---
language:
- af
- ar
- az
- be
- bg
- bn
- ca
- ceb
- cs
- cy
- da
- de
- el
- en
- es
- et
- eu
- fa
- fi
- fr
- gl
- gu
- he
- hi
- hr
- ht
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ky
- lo
- lt
- lv
- mk
- ml
- mn
- mr
- ms
- my
- ne
- nl
- 'no'
- pa
- pl
- pt
- qu
- ro
- ru
- si
- sk
- sl
- so
- sq
- sr
- sv
- sw
- ta
- te
- th
- tl
- tr
- uk
- ur
- vi
- yo
- zh
license: apache-2.0
model-index:
- name: gte-multilingual-base (dense)
  results:
  - dataset:
      config: default
      name: MTEB 8TagsClustering
      revision: None
      split: test
      type: PL-MTEB/8tags-clustering
    metrics:
    - type: v_measure
      value: 33.66681726329994
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB AFQMC
      revision: b44c3b011063adb25877c13823db83bb193913c4
      split: validation
      type: C-MTEB/AFQMC
    metrics:
    - type: cos_sim_spearman
      value: 43.54760696384009
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB ATEC
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
      split: test
      type: C-MTEB/ATEC
    metrics:
    - type: cos_sim_spearman
      value: 48.91186363417501
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB AllegroReviews
      revision: None
      split: test
      type: PL-MTEB/allegro-reviews
    metrics:
    - type: accuracy
      value: 41.689860834990064
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB AlloProfClusteringP2P
      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
      split: test
      type: lyon-nlp/alloprof
    metrics:
    - type: v_measure
      value: 54.20241337977897
    - type: v_measure
      value: 44.34083695608643
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB AlloprofReranking
      revision: 666fdacebe0291776e86f29345663dfaf80a0db9
      split: test
      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
    metrics:
    - type: map
      value: 64.91495250072002
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB AlloprofRetrieval
      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
      split: test
      type: lyon-nlp/alloprof
    metrics:
    - type: ndcg_at_10
      value: 53.638
    task:
      type: Retrieval
  - dataset:
      config: en
      name: MTEB AmazonCounterfactualClassification (en)
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      split: test
      type: mteb/amazon_counterfactual
    metrics:
    - type: accuracy
      value: 75.95522388059702
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB AmazonPolarityClassification
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
      split: test
      type: mteb/amazon_polarity
    metrics:
    - type: accuracy
      value: 80.717625
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB AmazonReviewsClassification (en)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 43.64199999999999
    task:
      type: Classification
  - dataset:
      config: de
      name: MTEB AmazonReviewsClassification (de)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 40.108
    task:
      type: Classification
  - dataset:
      config: es
      name: MTEB AmazonReviewsClassification (es)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 40.169999999999995
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB AmazonReviewsClassification (fr)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 39.56799999999999
    task:
      type: Classification
  - dataset:
      config: ja
      name: MTEB AmazonReviewsClassification (ja)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 35.75000000000001
    task:
      type: Classification
  - dataset:
      config: zh
      name: MTEB AmazonReviewsClassification (zh)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 33.342000000000006
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ArguAna
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
      split: test
      type: mteb/arguana
    metrics:
    - type: ndcg_at_10
      value: 58.231
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ArguAna-PL
      revision: 63fc86750af76253e8c760fc9e534bbf24d260a2
      split: test
      type: clarin-knext/arguana-pl
    metrics:
    - type: ndcg_at_10
      value: 53.166000000000004
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ArxivClusteringP2P
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
      split: test
      type: mteb/arxiv-clustering-p2p
    metrics:
    - type: v_measure
      value: 46.01900557959478
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ArxivClusteringS2S
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
      split: test
      type: mteb/arxiv-clustering-s2s
    metrics:
    - type: v_measure
      value: 41.06626465345723
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB AskUbuntuDupQuestions
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
      split: test
      type: mteb/askubuntudupquestions-reranking
    metrics:
    - type: map
      value: 61.87514497610431
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB BIOSSES
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
      split: test
      type: mteb/biosses-sts
    metrics:
    - type: cos_sim_spearman
      value: 81.21450112991194
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB BQ
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
      split: test
      type: C-MTEB/BQ
    metrics:
    - type: cos_sim_spearman
      value: 51.71589543397271
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB BSARDRetrieval
      revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
      split: test
      type: maastrichtlawtech/bsard
    metrics:
    - type: ndcg_at_10
      value: 26.115
    task:
      type: Retrieval
  - dataset:
      config: de-en
      name: MTEB BUCC (de-en)
      revision: d51519689f32196a32af33b075a01d0e7c51e252
      split: test
      type: mteb/bucc-bitext-mining
    metrics:
    - type: f1
      value: 98.6169102296451
    task:
      type: BitextMining
  - dataset:
      config: fr-en
      name: MTEB BUCC (fr-en)
      revision: d51519689f32196a32af33b075a01d0e7c51e252
      split: test
      type: mteb/bucc-bitext-mining
    metrics:
    - type: f1
      value: 97.89603052314916
    task:
      type: BitextMining
  - dataset:
      config: ru-en
      name: MTEB BUCC (ru-en)
      revision: d51519689f32196a32af33b075a01d0e7c51e252
      split: test
      type: mteb/bucc-bitext-mining
    metrics:
    - type: f1
      value: 97.12388869645537
    task:
      type: BitextMining
  - dataset:
      config: zh-en
      name: MTEB BUCC (zh-en)
      revision: d51519689f32196a32af33b075a01d0e7c51e252
      split: test
      type: mteb/bucc-bitext-mining
    metrics:
    - type: f1
      value: 98.15692469720906
    task:
      type: BitextMining
  - dataset:
      config: default
      name: MTEB Banking77Classification
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
      split: test
      type: mteb/banking77
    metrics:
    - type: accuracy
      value: 85.36038961038962
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB BiorxivClusteringP2P
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
      split: test
      type: mteb/biorxiv-clustering-p2p
    metrics:
    - type: v_measure
      value: 37.5903826674123
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB BiorxivClusteringS2S
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
      split: test
      type: mteb/biorxiv-clustering-s2s
    metrics:
    - type: v_measure
      value: 34.21474277151329
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CBD
      revision: None
      split: test
      type: PL-MTEB/cbd
    metrics:
    - type: accuracy
      value: 62.519999999999996
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB CDSC-E
      revision: None
      split: test
      type: PL-MTEB/cdsce-pairclassification
    metrics:
    - type: cos_sim_ap
      value: 74.90132799162956
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB CDSC-R
      revision: None
      split: test
      type: PL-MTEB/cdscr-sts
    metrics:
    - type: cos_sim_spearman
      value: 90.30727955142524
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB CLSClusteringP2P
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
      split: test
      type: C-MTEB/CLSClusteringP2P
    metrics:
    - type: v_measure
      value: 37.94850105022274
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CLSClusteringS2S
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
      split: test
      type: C-MTEB/CLSClusteringS2S
    metrics:
    - type: v_measure
      value: 38.11958675421534
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CMedQAv1
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
      split: test
      type: C-MTEB/CMedQAv1-reranking
    metrics:
    - type: map
      value: 86.10950950485399
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB CMedQAv2
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
      split: test
      type: C-MTEB/CMedQAv2-reranking
    metrics:
    - type: map
      value: 87.28038294231966
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB CQADupstackAndroidRetrieval
      revision: f46a197baaae43b4f621051089b82a364682dfeb
      split: test
      type: mteb/cqadupstack-android
    metrics:
    - type: ndcg_at_10
      value: 47.099000000000004
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackEnglishRetrieval
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
      split: test
      type: mteb/cqadupstack-english
    metrics:
    - type: ndcg_at_10
      value: 45.973000000000006
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackGamingRetrieval
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
      split: test
      type: mteb/cqadupstack-gaming
    metrics:
    - type: ndcg_at_10
      value: 55.606
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackGisRetrieval
      revision: 5003b3064772da1887988e05400cf3806fe491f2
      split: test
      type: mteb/cqadupstack-gis
    metrics:
    - type: ndcg_at_10
      value: 36.638
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackMathematicaRetrieval
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
      split: test
      type: mteb/cqadupstack-mathematica
    metrics:
    - type: ndcg_at_10
      value: 30.711
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackPhysicsRetrieval
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
      split: test
      type: mteb/cqadupstack-physics
    metrics:
    - type: ndcg_at_10
      value: 44.523
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackProgrammersRetrieval
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
      split: test
      type: mteb/cqadupstack-programmers
    metrics:
    - type: ndcg_at_10
      value: 37.940000000000005
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackRetrieval
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
      split: test
      type: mteb/cqadupstack
    metrics:
    - type: ndcg_at_10
      value: 38.12183333333333
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackStatsRetrieval
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
      split: test
      type: mteb/cqadupstack-stats
    metrics:
    - type: ndcg_at_10
      value: 32.684000000000005
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackTexRetrieval
      revision: 46989137a86843e03a6195de44b09deda022eec7
      split: test
      type: mteb/cqadupstack-tex
    metrics:
    - type: ndcg_at_10
      value: 26.735
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackUnixRetrieval
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
      split: test
      type: mteb/cqadupstack-unix
    metrics:
    - type: ndcg_at_10
      value: 36.933
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackWebmastersRetrieval
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
      split: test
      type: mteb/cqadupstack-webmasters
    metrics:
    - type: ndcg_at_10
      value: 33.747
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CQADupstackWordpressRetrieval
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
      split: test
      type: mteb/cqadupstack-wordpress
    metrics:
    - type: ndcg_at_10
      value: 28.872999999999998
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ClimateFEVER
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
      split: test
      type: mteb/climate-fever
    metrics:
    - type: ndcg_at_10
      value: 34.833
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB CmedqaRetrieval
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
      split: dev
      type: C-MTEB/CmedqaRetrieval
    metrics:
    - type: ndcg_at_10
      value: 43.78
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB Cmnli
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
      split: validation
      type: C-MTEB/CMNLI
    metrics:
    - type: cos_sim_ap
      value: 84.00640599186677
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB CovidRetrieval
      revision: 1271c7809071a13532e05f25fb53511ffce77117
      split: dev
      type: C-MTEB/CovidRetrieval
    metrics:
    - type: ndcg_at_10
      value: 80.60000000000001
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB DBPedia
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
      split: test
      type: mteb/dbpedia
    metrics:
    - type: ndcg_at_10
      value: 40.116
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB DBPedia-PL
      revision: 76afe41d9af165cc40999fcaa92312b8b012064a
      split: test
      type: clarin-knext/dbpedia-pl
    metrics:
    - type: ndcg_at_10
      value: 32.498
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB DuRetrieval
      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
      split: dev
      type: C-MTEB/DuRetrieval
    metrics:
    - type: ndcg_at_10
      value: 87.547
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB EcomRetrieval
      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
      split: dev
      type: C-MTEB/EcomRetrieval
    metrics:
    - type: ndcg_at_10
      value: 64.85
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB EmotionClassification
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
      split: test
      type: mteb/emotion
    metrics:
    - type: accuracy
      value: 47.949999999999996
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB FEVER
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
      split: test
      type: mteb/fever
    metrics:
    - type: ndcg_at_10
      value: 92.111
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB FiQA-PL
      revision: 2e535829717f8bf9dc829b7f911cc5bbd4e6608e
      split: test
      type: clarin-knext/fiqa-pl
    metrics:
    - type: ndcg_at_10
      value: 28.962
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB FiQA2018
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
      split: test
      type: mteb/fiqa
    metrics:
    - type: ndcg_at_10
      value: 45.005
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB HALClusteringS2S
      revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
      split: test
      type: lyon-nlp/clustering-hal-s2s
    metrics:
    - type: v_measure
      value: 25.133776435657595
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB HotpotQA
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
      split: test
      type: mteb/hotpotqa
    metrics:
    - type: ndcg_at_10
      value: 63.036
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB HotpotQA-PL
      revision: a0bd479ac97b4ccb5bd6ce320c415d0bb4beb907
      split: test
      type: clarin-knext/hotpotqa-pl
    metrics:
    - type: ndcg_at_10
      value: 56.904999999999994
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB IFlyTek
      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
      split: validation
      type: C-MTEB/IFlyTek-classification
    metrics:
    - type: accuracy
      value: 44.59407464409388
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ImdbClassification
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
      split: test
      type: mteb/imdb
    metrics:
    - type: accuracy
      value: 74.912
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB JDReview
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
      split: test
      type: C-MTEB/JDReview-classification
    metrics:
    - type: accuracy
      value: 79.26829268292683
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB LCQMC
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
      split: test
      type: C-MTEB/LCQMC
    metrics:
    - type: cos_sim_spearman
      value: 74.8601229809791
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB MLSUMClusteringP2P
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
      split: test
      type: mlsum
    metrics:
    - type: v_measure
      value: 42.331902754246556
    - type: v_measure
      value: 40.92029335502153
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MMarcoReranking
      revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
      split: dev
      type: C-MTEB/Mmarco-reranking
    metrics:
    - type: map
      value: 32.19266316591337
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB MMarcoRetrieval
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
      split: dev
      type: C-MTEB/MMarcoRetrieval
    metrics:
    - type: ndcg_at_10
      value: 79.346
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB MSMARCO
      revision: c5a29a104738b98a9e76336939199e264163d4a0
      split: dev
      type: mteb/msmarco
    metrics:
    - type: ndcg_at_10
      value: 39.922999999999995
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB MSMARCO-PL
      revision: 8634c07806d5cce3a6138e260e59b81760a0a640
      split: test
      type: clarin-knext/msmarco-pl
    metrics:
    - type: ndcg_at_10
      value: 55.620999999999995
    task:
      type: Retrieval
  - dataset:
      config: en
      name: MTEB MTOPDomainClassification (en)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 92.53989968080255
    task:
      type: Classification
  - dataset:
      config: de
      name: MTEB MTOPDomainClassification (de)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 88.26993519301212
    task:
      type: Classification
  - dataset:
      config: es
      name: MTEB MTOPDomainClassification (es)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 90.87725150100067
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB MTOPDomainClassification (fr)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 87.48512370811149
    task:
      type: Classification
  - dataset:
      config: hi
      name: MTEB MTOPDomainClassification (hi)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 89.45141627823591
    task:
      type: Classification
  - dataset:
      config: th
      name: MTEB MTOPDomainClassification (th)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 83.45750452079565
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MTOPIntentClassification (en)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 72.57637938896488
    task:
      type: Classification
  - dataset:
      config: de
      name: MTEB MTOPIntentClassification (de)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 63.50803043110736
    task:
      type: Classification
  - dataset:
      config: es
      name: MTEB MTOPIntentClassification (es)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 71.6577718478986
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB MTOPIntentClassification (fr)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 64.05887879736925
    task:
      type: Classification
  - dataset:
      config: hi
      name: MTEB MTOPIntentClassification (hi)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 65.27070634636071
    task:
      type: Classification
  - dataset:
      config: th
      name: MTEB MTOPIntentClassification (th)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 63.04520795660037
    task:
      type: Classification
  - dataset:
      config: fra
      name: MTEB MasakhaNEWSClassification (fra)
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
      split: test
      type: masakhane/masakhanews
    metrics:
    - type: accuracy
      value: 80.66350710900474
    task:
      type: Classification
  - dataset:
      config: fra
      name: MTEB MasakhaNEWSClusteringP2P (fra)
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
      split: test
      type: masakhane/masakhanews
    metrics:
    - type: v_measure
      value: 44.016506455899425
    - type: v_measure
      value: 40.67730129573544
    task:
      type: Clustering
  - dataset:
      config: af
      name: MTEB MassiveIntentClassification (af)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 57.94552790854068
    task:
      type: Classification
  - dataset:
      config: am
      name: MTEB MassiveIntentClassification (am)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 49.273705447209146
    task:
      type: Classification
  - dataset:
      config: ar
      name: MTEB MassiveIntentClassification (ar)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 55.490921318090116
    task:
      type: Classification
  - dataset:
      config: az
      name: MTEB MassiveIntentClassification (az)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 60.97511768661733
    task:
      type: Classification
  - dataset:
      config: bn
      name: MTEB MassiveIntentClassification (bn)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 57.5689307330195
    task:
      type: Classification
  - dataset:
      config: cy
      name: MTEB MassiveIntentClassification (cy)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 48.34902488231337
    task:
      type: Classification
  - dataset:
      config: da
      name: MTEB MassiveIntentClassification (da)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 63.6684599865501
    task:
      type: Classification
  - dataset:
      config: de
      name: MTEB MassiveIntentClassification (de)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 62.54539340954942
    task:
      type: Classification
  - dataset:
      config: el
      name: MTEB MassiveIntentClassification (el)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 63.08675184936112
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveIntentClassification (en)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 72.12508406186953
    task:
      type: Classification
  - dataset:
      config: es
      name: MTEB MassiveIntentClassification (es)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 67.41425689307331
    task:
      type: Classification
  - dataset:
      config: fa
      name: MTEB MassiveIntentClassification (fa)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 65.59515803631474
    task:
      type: Classification
  - dataset:
      config: fi
      name: MTEB MassiveIntentClassification (fi)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 62.90517821116342
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB MassiveIntentClassification (fr)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 67.91526563550774
    task:
      type: Classification
  - dataset:
      config: he
      name: MTEB MassiveIntentClassification (he)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 55.198386012104905
    task:
      type: Classification
  - dataset:
      config: hi
      name: MTEB MassiveIntentClassification (hi)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 65.04371217215869
    task:
      type: Classification
  - dataset:
      config: hu
      name: MTEB MassiveIntentClassification (hu)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 63.31203765971756
    task:
      type: Classification
  - dataset:
      config: hy
      name: MTEB MassiveIntentClassification (hy)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 55.521183591123055
    task:
      type: Classification
  - dataset:
      config: id
      name: MTEB MassiveIntentClassification (id)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 66.06254203093476
    task:
      type: Classification
  - dataset:
      config: is
      name: MTEB MassiveIntentClassification (is)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 56.01546738399461
    task:
      type: Classification
  - dataset:
      config: it
      name: MTEB MassiveIntentClassification (it)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 67.27975790181574
    task:
      type: Classification
  - dataset:
      config: ja
      name: MTEB MassiveIntentClassification (ja)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 66.79556153328849
    task:
      type: Classification
  - dataset:
      config: jv
      name: MTEB MassiveIntentClassification (jv)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 50.18493611297915
    task:
      type: Classification
  - dataset:
      config: ka
      name: MTEB MassiveIntentClassification (ka)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 47.888365837256224
    task:
      type: Classification
  - dataset:
      config: km
      name: MTEB MassiveIntentClassification (km)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 50.79690652320108
    task:
      type: Classification
  - dataset:
      config: kn
      name: MTEB MassiveIntentClassification (kn)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 57.225958305312716
    task:
      type: Classification
  - dataset:
      config: ko
      name: MTEB MassiveIntentClassification (ko)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 64.58641560188299
    task:
      type: Classification
  - dataset:
      config: lv
      name: MTEB MassiveIntentClassification (lv)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 59.08204438466711
    task:
      type: Classification
  - dataset:
      config: ml
      name: MTEB MassiveIntentClassification (ml)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 59.54606590450572
    task:
      type: Classification
  - dataset:
      config: mn
      name: MTEB MassiveIntentClassification (mn)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 53.443174176193665
    task:
      type: Classification
  - dataset:
      config: ms
      name: MTEB MassiveIntentClassification (ms)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 61.65097511768661
    task:
      type: Classification
  - dataset:
      config: my
      name: MTEB MassiveIntentClassification (my)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 53.45662407531944
    task:
      type: Classification
  - dataset:
      config: nb
      name: MTEB MassiveIntentClassification (nb)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 63.739071956960316
    task:
      type: Classification
  - dataset:
      config: nl
      name: MTEB MassiveIntentClassification (nl)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 66.36180228648286
    task:
      type: Classification
  - dataset:
      config: pl
      name: MTEB MassiveIntentClassification (pl)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 66.3920645595158
    task:
      type: Classification
  - dataset:
      config: pt
      name: MTEB MassiveIntentClassification (pt)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 68.06993947545395
    task:
      type: Classification
  - dataset:
      config: ro
      name: MTEB MassiveIntentClassification (ro)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 63.123739071956955
    task:
      type: Classification
  - dataset:
      config: ru
      name: MTEB MassiveIntentClassification (ru)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 67.46133154001346
    task:
      type: Classification
  - dataset:
      config: sl
      name: MTEB MassiveIntentClassification (sl)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 60.54472091459314
    task:
      type: Classification
  - dataset:
      config: sq
      name: MTEB MassiveIntentClassification (sq)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 58.204438466711494
    task:
      type: Classification
  - dataset:
      config: sv
      name: MTEB MassiveIntentClassification (sv)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 65.69603227975792
    task:
      type: Classification
  - dataset:
      config: sw
      name: MTEB MassiveIntentClassification (sw)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 51.684599865501
    task:
      type: Classification
  - dataset:
      config: ta
      name: MTEB MassiveIntentClassification (ta)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 58.523873570948226
    task:
      type: Classification
  - dataset:
      config: te
      name: MTEB MassiveIntentClassification (te)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 58.53396099529253
    task:
      type: Classification
  - dataset:
      config: th
      name: MTEB MassiveIntentClassification (th)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 61.88298587760591
    task:
      type: Classification
  - dataset:
      config: tl
      name: MTEB MassiveIntentClassification (tl)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 56.65097511768662
    task:
      type: Classification
  - dataset:
      config: tr
      name: MTEB MassiveIntentClassification (tr)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 64.8453261600538
    task:
      type: Classification
  - dataset:
      config: ur
      name: MTEB MassiveIntentClassification (ur)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 58.6247478143914
    task:
      type: Classification
  - dataset:
      config: vi
      name: MTEB MassiveIntentClassification (vi)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 64.16274377942166
    task:
      type: Classification
  - dataset:
      config: zh-CN
      name: MTEB MassiveIntentClassification (zh-CN)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 69.61667787491594
    task:
      type: Classification
  - dataset:
      config: zh-TW
      name: MTEB MassiveIntentClassification (zh-TW)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 64.17283120376598
    task:
      type: Classification
  - dataset:
      config: af
      name: MTEB MassiveScenarioClassification (af)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 64.89912575655683
    task:
      type: Classification
  - dataset:
      config: am
      name: MTEB MassiveScenarioClassification (am)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 57.27975790181573
    task:
      type: Classification
  - dataset:
      config: ar
      name: MTEB MassiveScenarioClassification (ar)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 62.269670477471415
    task:
      type: Classification
  - dataset:
      config: az
      name: MTEB MassiveScenarioClassification (az)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 65.10423671822461
    task:
      type: Classification
  - dataset:
      config: bn
      name: MTEB MassiveScenarioClassification (bn)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 62.40753194351043
    task:
      type: Classification
  - dataset:
      config: cy
      name: MTEB MassiveScenarioClassification (cy)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 55.369872225958304
    task:
      type: Classification
  - dataset:
      config: da
      name: MTEB MassiveScenarioClassification (da)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.60726294552792
    task:
      type: Classification
  - dataset:
      config: de
      name: MTEB MassiveScenarioClassification (de)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 70.30262273032952
    task:
      type: Classification
  - dataset:
      config: el
      name: MTEB MassiveScenarioClassification (el)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 69.52925353059851
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveScenarioClassification (en)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 76.28446536650976
    task:
      type: Classification
  - dataset:
      config: es
      name: MTEB MassiveScenarioClassification (es)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 72.45460659045058
    task:
      type: Classification
  - dataset:
      config: fa
      name: MTEB MassiveScenarioClassification (fa)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 70.26563550773368
    task:
      type: Classification
  - dataset:
      config: fi
      name: MTEB MassiveScenarioClassification (fi)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 67.20578345662408
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB MassiveScenarioClassification (fr)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 72.64963012777405
    task:
      type: Classification
  - dataset:
      config: he
      name: MTEB MassiveScenarioClassification (he)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 61.698049764626774
    task:
      type: Classification
  - dataset:
      config: hi
      name: MTEB MassiveScenarioClassification (hi)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 70.14458641560188
    task:
      type: Classification
  - dataset:
      config: hu
      name: MTEB MassiveScenarioClassification (hu)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 70.51445864156018
    task:
      type: Classification
  - dataset:
      config: hy
      name: MTEB MassiveScenarioClassification (hy)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 60.13786146603901
    task:
      type: Classification
  - dataset:
      config: id
      name: MTEB MassiveScenarioClassification (id)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 70.61533288500337
    task:
      type: Classification
  - dataset:
      config: is
      name: MTEB MassiveScenarioClassification (is)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 61.526563550773375
    task:
      type: Classification
  - dataset:
      config: it
      name: MTEB MassiveScenarioClassification (it)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.99731002017484
    task:
      type: Classification
  - dataset:
      config: ja
      name: MTEB MassiveScenarioClassification (ja)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.59381304640216
    task:
      type: Classification
  - dataset:
      config: jv
      name: MTEB MassiveScenarioClassification (jv)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 57.010759919300604
    task:
      type: Classification
  - dataset:
      config: ka
      name: MTEB MassiveScenarioClassification (ka)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 53.26160053799597
    task:
      type: Classification
  - dataset:
      config: km
      name: MTEB MassiveScenarioClassification (km)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 57.800941492938804
    task:
      type: Classification
  - dataset:
      config: kn
      name: MTEB MassiveScenarioClassification (kn)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 62.387357094821795
    task:
      type: Classification
  - dataset:
      config: ko
      name: MTEB MassiveScenarioClassification (ko)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 69.5359784801614
    task:
      type: Classification
  - dataset:
      config: lv
      name: MTEB MassiveScenarioClassification (lv)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 63.36919973100203
    task:
      type: Classification
  - dataset:
      config: ml
      name: MTEB MassiveScenarioClassification (ml)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 64.81506388702084
    task:
      type: Classification
  - dataset:
      config: mn
      name: MTEB MassiveScenarioClassification (mn)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 59.35104236718225
    task:
      type: Classification
  - dataset:
      config: ms
      name: MTEB MassiveScenarioClassification (ms)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 66.67787491593813
    task:
      type: Classification
  - dataset:
      config: my
      name: MTEB MassiveScenarioClassification (my)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 59.4250168123739
    task:
      type: Classification
  - dataset:
      config: nb
      name: MTEB MassiveScenarioClassification (nb)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.49630127774043
    task:
      type: Classification
  - dataset:
      config: nl
      name: MTEB MassiveScenarioClassification (nl)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.95696032279758
    task:
      type: Classification
  - dataset:
      config: pl
      name: MTEB MassiveScenarioClassification (pl)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 70.11768661735036
    task:
      type: Classification
  - dataset:
      config: pt
      name: MTEB MassiveScenarioClassification (pt)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.86953597848016
    task:
      type: Classification
  - dataset:
      config: ro
      name: MTEB MassiveScenarioClassification (ro)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 68.51042367182247
    task:
      type: Classification
  - dataset:
      config: ru
      name: MTEB MassiveScenarioClassification (ru)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.65097511768661
    task:
      type: Classification
  - dataset:
      config: sl
      name: MTEB MassiveScenarioClassification (sl)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 66.81573638197713
    task:
      type: Classification
  - dataset:
      config: sq
      name: MTEB MassiveScenarioClassification (sq)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 65.26227303295225
    task:
      type: Classification
  - dataset:
      config: sv
      name: MTEB MassiveScenarioClassification (sv)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 72.51513113651646
    task:
      type: Classification
  - dataset:
      config: sw
      name: MTEB MassiveScenarioClassification (sw)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 58.29858776059179
    task:
      type: Classification
  - dataset:
      config: ta
      name: MTEB MassiveScenarioClassification (ta)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 62.72696704774714
    task:
      type: Classification
  - dataset:
      config: te
      name: MTEB MassiveScenarioClassification (te)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 66.57700067249496
    task:
      type: Classification
  - dataset:
      config: th
      name: MTEB MassiveScenarioClassification (th)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 68.22797579018157
    task:
      type: Classification
  - dataset:
      config: tl
      name: MTEB MassiveScenarioClassification (tl)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 61.97041022192333
    task:
      type: Classification
  - dataset:
      config: tr
      name: MTEB MassiveScenarioClassification (tr)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 70.72629455279085
    task:
      type: Classification
  - dataset:
      config: ur
      name: MTEB MassiveScenarioClassification (ur)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 63.16072629455278
    task:
      type: Classification
  - dataset:
      config: vi
      name: MTEB MassiveScenarioClassification (vi)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 67.92199058507062
    task:
      type: Classification
  - dataset:
      config: zh-CN
      name: MTEB MassiveScenarioClassification (zh-CN)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 74.40484196368527
    task:
      type: Classification
  - dataset:
      config: zh-TW
      name: MTEB MassiveScenarioClassification (zh-TW)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 71.61398789509079
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB MedicalRetrieval
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
      split: dev
      type: C-MTEB/MedicalRetrieval
    metrics:
    - type: ndcg_at_10
      value: 61.934999999999995
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB MedrxivClusteringP2P
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
      split: test
      type: mteb/medrxiv-clustering-p2p
    metrics:
    - type: v_measure
      value: 33.052031054565205
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MedrxivClusteringS2S
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
      split: test
      type: mteb/medrxiv-clustering-s2s
    metrics:
    - type: v_measure
      value: 31.969909524076794
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MindSmallReranking
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
      split: test
      type: mteb/mind_small
    metrics:
    - type: map
      value: 31.7530992892652
    task:
      type: Reranking
  - dataset:
      config: fr
      name: MTEB MintakaRetrieval (fr)
      revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
      split: test
      type: jinaai/mintakaqa
    metrics:
    - type: ndcg_at_10
      value: 34.705999999999996
    task:
      type: Retrieval
  - dataset:
      config: ar
      name: MTEB MultiLongDocRetrieval (ar)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 55.166000000000004
    task:
      type: Retrieval
  - dataset:
      config: de
      name: MTEB MultiLongDocRetrieval (de)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 55.155
    task:
      type: Retrieval
  - dataset:
      config: en
      name: MTEB MultiLongDocRetrieval (en)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 50.993
    task:
      type: Retrieval
  - dataset:
      config: es
      name: MTEB MultiLongDocRetrieval (es)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 81.228
    task:
      type: Retrieval
  - dataset:
      config: fr
      name: MTEB MultiLongDocRetrieval (fr)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 76.19
    task:
      type: Retrieval
  - dataset:
      config: hi
      name: MTEB MultiLongDocRetrieval (hi)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 45.206
    task:
      type: Retrieval
  - dataset:
      config: it
      name: MTEB MultiLongDocRetrieval (it)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 66.741
    task:
      type: Retrieval
  - dataset:
      config: ja
      name: MTEB MultiLongDocRetrieval (ja)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 52.111
    task:
      type: Retrieval
  - dataset:
      config: ko
      name: MTEB MultiLongDocRetrieval (ko)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 46.733000000000004
    task:
      type: Retrieval
  - dataset:
      config: pt
      name: MTEB MultiLongDocRetrieval (pt)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 79.105
    task:
      type: Retrieval
  - dataset:
      config: ru
      name: MTEB MultiLongDocRetrieval (ru)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 64.21
    task:
      type: Retrieval
  - dataset:
      config: th
      name: MTEB MultiLongDocRetrieval (th)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 35.467
    task:
      type: Retrieval
  - dataset:
      config: zh
      name: MTEB MultiLongDocRetrieval (zh)
      revision: None
      split: test
      type: Shitao/MLDR
    metrics:
    - type: ndcg_at_10
      value: 27.419
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB MultilingualSentiment
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
      split: validation
      type: C-MTEB/MultilingualSentiment-classification
    metrics:
    - type: accuracy
      value: 61.02000000000001
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB NFCorpus
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
      split: test
      type: mteb/nfcorpus
    metrics:
    - type: ndcg_at_10
      value: 36.65
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB NFCorpus-PL
      revision: 9a6f9567fda928260afed2de480d79c98bf0bec0
      split: test
      type: clarin-knext/nfcorpus-pl
    metrics:
    - type: ndcg_at_10
      value: 26.831
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB NQ
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
      split: test
      type: mteb/nq
    metrics:
    - type: ndcg_at_10
      value: 58.111000000000004
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB NQ-PL
      revision: f171245712cf85dd4700b06bef18001578d0ca8d
      split: test
      type: clarin-knext/nq-pl
    metrics:
    - type: ndcg_at_10
      value: 43.126999999999995
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB Ocnli
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
      split: validation
      type: C-MTEB/OCNLI
    metrics:
    - type: cos_sim_ap
      value: 72.67630697316041
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB OnlineShopping
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
      split: test
      type: C-MTEB/OnlineShopping-classification
    metrics:
    - type: accuracy
      value: 84.85000000000001
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB OpusparcusPC (fr)
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
      split: test
      type: GEM/opusparcus
    metrics:
    - type: cos_sim_ap
      value: 100
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB PAC
      revision: None
      split: test
      type: laugustyniak/abusive-clauses-pl
    metrics:
    - type: accuracy
      value: 65.99189110918043
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB PAWSX
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
      split: test
      type: C-MTEB/PAWSX
    metrics:
    - type: cos_sim_spearman
      value: 16.124364530596228
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB PPC
      revision: None
      split: test
      type: PL-MTEB/ppc-pairclassification
    metrics:
    - type: cos_sim_ap
      value: 92.43431057460192
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB PSC
      revision: None
      split: test
      type: PL-MTEB/psc-pairclassification
    metrics:
    - type: cos_sim_ap
      value: 99.06090138049724
    task:
      type: PairClassification
  - dataset:
      config: fr
      name: MTEB PawsX (fr)
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
      split: test
      type: paws-x
    metrics:
    - type: cos_sim_ap
      value: 58.9314954874314
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB PolEmo2.0-IN
      revision: None
      split: test
      type: PL-MTEB/polemo2_in
    metrics:
    - type: accuracy
      value: 69.59833795013851
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB PolEmo2.0-OUT
      revision: None
      split: test
      type: PL-MTEB/polemo2_out
    metrics:
    - type: accuracy
      value: 44.73684210526315
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB QBQTC
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
      split: test
      type: C-MTEB/QBQTC
    metrics:
    - type: cos_sim_spearman
      value: 39.36450754137984
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB Quora-PL
      revision: 0be27e93455051e531182b85e85e425aba12e9d4
      split: test
      type: clarin-knext/quora-pl
    metrics:
    - type: ndcg_at_10
      value: 80.76299999999999
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB QuoraRetrieval
      revision: None
      split: test
      type: mteb/quora
    metrics:
    - type: ndcg_at_10
      value: 88.022
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB RedditClustering
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
      split: test
      type: mteb/reddit-clustering
    metrics:
    - type: v_measure
      value: 55.719165988934385
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB RedditClusteringP2P
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
      split: test
      type: mteb/reddit-clustering-p2p
    metrics:
    - type: v_measure
      value: 62.25390069273025
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB SCIDOCS
      revision: None
      split: test
      type: mteb/scidocs
    metrics:
    - type: ndcg_at_10
      value: 18.243000000000002
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SCIDOCS-PL
      revision: 45452b03f05560207ef19149545f168e596c9337
      split: test
      type: clarin-knext/scidocs-pl
    metrics:
    - type: ndcg_at_10
      value: 14.219000000000001
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SICK-E-PL
      revision: None
      split: test
      type: PL-MTEB/sicke-pl-pairclassification
    metrics:
    - type: cos_sim_ap
      value: 75.4022630307816
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB SICK-R
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
      split: test
      type: mteb/sickr-sts
    metrics:
    - type: cos_sim_spearman
      value: 79.34269390198548
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SICK-R-PL
      revision: None
      split: test
      type: PL-MTEB/sickr-pl-sts
    metrics:
    - type: cos_sim_spearman
      value: 74.0651660446132
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SICKFr
      revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
      split: test
      type: Lajavaness/SICK-fr
    metrics:
    - type: cos_sim_spearman
      value: 78.62693119733123
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS12
      revision: a0d554a64d88156834ff5ae9920b964011b16384
      split: test
      type: mteb/sts12-sts
    metrics:
    - type: cos_sim_spearman
      value: 77.50660544631359
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS13
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
      split: test
      type: mteb/sts13-sts
    metrics:
    - type: cos_sim_spearman
      value: 85.55415077723738
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS14
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
      split: test
      type: mteb/sts14-sts
    metrics:
    - type: cos_sim_spearman
      value: 81.67550814479077
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS15
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
      split: test
      type: mteb/sts15-sts
    metrics:
    - type: cos_sim_spearman
      value: 88.94601412322764
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS16
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
      split: test
      type: mteb/sts16-sts
    metrics:
    - type: cos_sim_spearman
      value: 84.33844259337481
    task:
      type: STS
  - dataset:
      config: ko-ko
      name: MTEB STS17 (ko-ko)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 81.58650681159105
    task:
      type: STS
  - dataset:
      config: ar-ar
      name: MTEB STS17 (ar-ar)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 78.82472265884256
    task:
      type: STS
  - dataset:
      config: en-ar
      name: MTEB STS17 (en-ar)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 76.43637938260397
    task:
      type: STS
  - dataset:
      config: en-de
      name: MTEB STS17 (en-de)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 84.71008299464059
    task:
      type: STS
  - dataset:
      config: en-en
      name: MTEB STS17 (en-en)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 88.88074713413747
    task:
      type: STS
  - dataset:
      config: en-tr
      name: MTEB STS17 (en-tr)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 76.36405640457285
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS17 (es-en)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 83.84737910084762
    task:
      type: STS
  - dataset:
      config: es-es
      name: MTEB STS17 (es-es)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 87.03931621433031
    task:
      type: STS
  - dataset:
      config: fr-en
      name: MTEB STS17 (fr-en)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 84.43335591752246
    task:
      type: STS
  - dataset:
      config: it-en
      name: MTEB STS17 (it-en)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 83.85268648747021
    task:
      type: STS
  - dataset:
      config: nl-en
      name: MTEB STS17 (nl-en)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 82.45786516224341
    task:
      type: STS
  - dataset:
      config: en
      name: MTEB STS22 (en)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 67.20227303970304
    task:
      type: STS
  - dataset:
      config: de
      name: MTEB STS22 (de)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 60.892838305537126
    task:
      type: STS
  - dataset:
      config: es
      name: MTEB STS22 (es)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 72.01876318464508
    task:
      type: STS
  - dataset:
      config: pl
      name: MTEB STS22 (pl)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 42.3879320510127
    task:
      type: STS
  - dataset:
      config: tr
      name: MTEB STS22 (tr)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 65.54048784845729
    task:
      type: STS
  - dataset:
      config: ar
      name: MTEB STS22 (ar)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 58.55244068334867
    task:
      type: STS
  - dataset:
      config: ru
      name: MTEB STS22 (ru)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 66.48710288440624
    task:
      type: STS
  - dataset:
      config: zh
      name: MTEB STS22 (zh)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 66.585754901838
    task:
      type: STS
  - dataset:
      config: fr
      name: MTEB STS22 (fr)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 81.03001290557805
    task:
      type: STS
  - dataset:
      config: de-en
      name: MTEB STS22 (de-en)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 62.28001859884359
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS22 (es-en)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 79.64106342105019
    task:
      type: STS
  - dataset:
      config: it
      name: MTEB STS22 (it)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 78.27915339361124
    task:
      type: STS
  - dataset:
      config: pl-en
      name: MTEB STS22 (pl-en)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 78.28574268257462
    task:
      type: STS
  - dataset:
      config: zh-en
      name: MTEB STS22 (zh-en)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 72.92658860751482
    task:
      type: STS
  - dataset:
      config: es-it
      name: MTEB STS22 (es-it)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 74.83418886368217
    task:
      type: STS
  - dataset:
      config: de-fr
      name: MTEB STS22 (de-fr)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 56.01064022625769
    task:
      type: STS
  - dataset:
      config: de-pl
      name: MTEB STS22 (de-pl)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 53.64332829635126
    task:
      type: STS
  - dataset:
      config: fr-pl
      name: MTEB STS22 (fr-pl)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cos_sim_spearman
      value: 73.24670207647144
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSB
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
      split: test
      type: C-MTEB/STSB
    metrics:
    - type: cos_sim_spearman
      value: 80.7157790971544
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSBenchmark
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
      split: test
      type: mteb/stsbenchmark-sts
    metrics:
    - type: cos_sim_spearman
      value: 86.45763616928973
    task:
      type: STS
  - dataset:
      config: fr
      name: MTEB STSBenchmarkMultilingualSTS (fr)
      revision: 93d57ef91790589e3ce9c365164337a8a78b7632
      split: test
      type: stsb_multi_mt
    metrics:
    - type: cos_sim_spearman
      value: 84.4335500335282
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SciDocsRR
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
      split: test
      type: mteb/scidocs-reranking
    metrics:
    - type: map
      value: 84.15276484499303
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SciFact
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
      split: test
      type: mteb/scifact
    metrics:
    - type: ndcg_at_10
      value: 73.433
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SciFact-PL
      revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e
      split: test
      type: clarin-knext/scifact-pl
    metrics:
    - type: ndcg_at_10
      value: 58.919999999999995
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SprintDuplicateQuestions
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
      split: test
      type: mteb/sprintduplicatequestions-pairclassification
    metrics:
    - type: cos_sim_ap
      value: 95.40564890916419
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB StackExchangeClustering
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
      split: test
      type: mteb/stackexchange-clustering
    metrics:
    - type: v_measure
      value: 63.41856697730145
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackExchangeClusteringP2P
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
      split: test
      type: mteb/stackexchange-clustering-p2p
    metrics:
    - type: v_measure
      value: 31.709285904909112
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackOverflowDupQuestions
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
      split: test
      type: mteb/stackoverflowdupquestions-reranking
    metrics:
    - type: map
      value: 52.09341030060322
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SummEval
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
      split: test
      type: mteb/summeval
    metrics:
    - type: cos_sim_spearman
      value: 30.58262517835034
    task:
      type: Summarization
  - dataset:
      config: default
      name: MTEB SummEvalFr
      revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
      split: test
      type: lyon-nlp/summarization-summeval-fr-p2p
    metrics:
    - type: cos_sim_spearman
      value: 29.744542072951358
    task:
      type: Summarization
  - dataset:
      config: default
      name: MTEB SyntecReranking
      revision: b205c5084a0934ce8af14338bf03feb19499c84d
      split: test
      type: lyon-nlp/mteb-fr-reranking-syntec-s2p
    metrics:
    - type: map
      value: 88.03333333333333
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SyntecRetrieval
      revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff
      split: test
      type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
    metrics:
    - type: ndcg_at_10
      value: 83.043
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB T2Reranking
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
      split: dev
      type: C-MTEB/T2Reranking
    metrics:
    - type: map
      value: 67.08577894804324
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB T2Retrieval
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
      split: dev
      type: C-MTEB/T2Retrieval
    metrics:
    - type: ndcg_at_10
      value: 84.718
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB TNews
      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
      split: validation
      type: C-MTEB/TNews-classification
    metrics:
    - type: accuracy
      value: 48.726
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TRECCOVID
      revision: None
      split: test
      type: mteb/trec-covid
    metrics:
    - type: ndcg_at_10
      value: 57.56
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB TRECCOVID-PL
      revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd
      split: test
      type: clarin-knext/trec-covid-pl
    metrics:
    - type: ndcg_at_10
      value: 59.355999999999995
    task:
      type: Retrieval
  - dataset:
      config: sqi-eng
      name: MTEB Tatoeba (sqi-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 82.765
    task:
      type: BitextMining
  - dataset:
      config: fry-eng
      name: MTEB Tatoeba (fry-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 73.69942196531792
    task:
      type: BitextMining
  - dataset:
      config: kur-eng
      name: MTEB Tatoeba (kur-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 32.86585365853657
    task:
      type: BitextMining
  - dataset:
      config: tur-eng
      name: MTEB Tatoeba (tur-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 95.81666666666666
    task:
      type: BitextMining
  - dataset:
      config: deu-eng
      name: MTEB Tatoeba (deu-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 97.75
    task:
      type: BitextMining
  - dataset:
      config: nld-eng
      name: MTEB Tatoeba (nld-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 93.78333333333335
    task:
      type: BitextMining
  - dataset:
      config: ron-eng
      name: MTEB Tatoeba (ron-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 90.72333333333333
    task:
      type: BitextMining
  - dataset:
      config: ang-eng
      name: MTEB Tatoeba (ang-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 42.45202558635395
    task:
      type: BitextMining
  - dataset:
      config: ido-eng
      name: MTEB Tatoeba (ido-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 77.59238095238095
    task:
      type: BitextMining
  - dataset:
      config: jav-eng
      name: MTEB Tatoeba (jav-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 35.69686411149825
    task:
      type: BitextMining
  - dataset:
      config: isl-eng
      name: MTEB Tatoeba (isl-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 82.59333333333333
    task:
      type: BitextMining
  - dataset:
      config: slv-eng
      name: MTEB Tatoeba (slv-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 84.1456922987907
    task:
      type: BitextMining
  - dataset:
      config: cym-eng
      name: MTEB Tatoeba (cym-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 52.47462133594857
    task:
      type: BitextMining
  - dataset:
      config: kaz-eng
      name: MTEB Tatoeba (kaz-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 67.62965440356746
    task:
      type: BitextMining
  - dataset:
      config: est-eng
      name: MTEB Tatoeba (est-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 79.48412698412699
    task:
      type: BitextMining
  - dataset:
      config: heb-eng
      name: MTEB Tatoeba (heb-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 75.85
    task:
      type: BitextMining
  - dataset:
      config: gla-eng
      name: MTEB Tatoeba (gla-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 27.32600866497127
    task:
      type: BitextMining
  - dataset:
      config: mar-eng
      name: MTEB Tatoeba (mar-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 84.38
    task:
      type: BitextMining
  - dataset:
      config: lat-eng
      name: MTEB Tatoeba (lat-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 42.98888712165028
    task:
      type: BitextMining
  - dataset:
      config: bel-eng
      name: MTEB Tatoeba (bel-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 85.55690476190476
    task:
      type: BitextMining
  - dataset:
      config: pms-eng
      name: MTEB Tatoeba (pms-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 46.68466031323174
    task:
      type: BitextMining
  - dataset:
      config: gle-eng
      name: MTEB Tatoeba (gle-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 32.73071428571428
    task:
      type: BitextMining
  - dataset:
      config: pes-eng
      name: MTEB Tatoeba (pes-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 88.26333333333334
    task:
      type: BitextMining
  - dataset:
      config: nob-eng
      name: MTEB Tatoeba (nob-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 96.61666666666666
    task:
      type: BitextMining
  - dataset:
      config: bul-eng
      name: MTEB Tatoeba (bul-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.30666666666666
    task:
      type: BitextMining
  - dataset:
      config: cbk-eng
      name: MTEB Tatoeba (cbk-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 70.03714285714285
    task:
      type: BitextMining
  - dataset:
      config: hun-eng
      name: MTEB Tatoeba (hun-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 89.09
    task:
      type: BitextMining
  - dataset:
      config: uig-eng
      name: MTEB Tatoeba (uig-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 59.570476190476185
    task:
      type: BitextMining
  - dataset:
      config: rus-eng
      name: MTEB Tatoeba (rus-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 92.9
    task:
      type: BitextMining
  - dataset:
      config: spa-eng
      name: MTEB Tatoeba (spa-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 97.68333333333334
    task:
      type: BitextMining
  - dataset:
      config: hye-eng
      name: MTEB Tatoeba (hye-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 80.40880503144653
    task:
      type: BitextMining
  - dataset:
      config: tel-eng
      name: MTEB Tatoeba (tel-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 89.7008547008547
    task:
      type: BitextMining
  - dataset:
      config: afr-eng
      name: MTEB Tatoeba (afr-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 81.84833333333333
    task:
      type: BitextMining
  - dataset:
      config: mon-eng
      name: MTEB Tatoeba (mon-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 71.69696969696969
    task:
      type: BitextMining
  - dataset:
      config: arz-eng
      name: MTEB Tatoeba (arz-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 55.76985790822269
    task:
      type: BitextMining
  - dataset:
      config: hrv-eng
      name: MTEB Tatoeba (hrv-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.66666666666666
    task:
      type: BitextMining
  - dataset:
      config: nov-eng
      name: MTEB Tatoeba (nov-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 68.36668519547896
    task:
      type: BitextMining
  - dataset:
      config: gsw-eng
      name: MTEB Tatoeba (gsw-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 36.73992673992674
    task:
      type: BitextMining
  - dataset:
      config: nds-eng
      name: MTEB Tatoeba (nds-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 63.420952380952365
    task:
      type: BitextMining
  - dataset:
      config: ukr-eng
      name: MTEB Tatoeba (ukr-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.28999999999999
    task:
      type: BitextMining
  - dataset:
      config: uzb-eng
      name: MTEB Tatoeba (uzb-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 40.95392490046146
    task:
      type: BitextMining
  - dataset:
      config: lit-eng
      name: MTEB Tatoeba (lit-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 77.58936507936508
    task:
      type: BitextMining
  - dataset:
      config: ina-eng
      name: MTEB Tatoeba (ina-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.28999999999999
    task:
      type: BitextMining
  - dataset:
      config: lfn-eng
      name: MTEB Tatoeba (lfn-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 63.563650793650794
    task:
      type: BitextMining
  - dataset:
      config: zsm-eng
      name: MTEB Tatoeba (zsm-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 94.35
    task:
      type: BitextMining
  - dataset:
      config: ita-eng
      name: MTEB Tatoeba (ita-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.43
    task:
      type: BitextMining
  - dataset:
      config: cmn-eng
      name: MTEB Tatoeba (cmn-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 95.73333333333332
    task:
      type: BitextMining
  - dataset:
      config: lvs-eng
      name: MTEB Tatoeba (lvs-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 79.38666666666667
    task:
      type: BitextMining
  - dataset:
      config: glg-eng
      name: MTEB Tatoeba (glg-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 89.64
    task:
      type: BitextMining
  - dataset:
      config: ceb-eng
      name: MTEB Tatoeba (ceb-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 21.257184628237262
    task:
      type: BitextMining
  - dataset:
      config: bre-eng
      name: MTEB Tatoeba (bre-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 13.592316017316017
    task:
      type: BitextMining
  - dataset:
      config: ben-eng
      name: MTEB Tatoeba (ben-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 73.22666666666666
    task:
      type: BitextMining
  - dataset:
      config: swg-eng
      name: MTEB Tatoeba (swg-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 51.711309523809526
    task:
      type: BitextMining
  - dataset:
      config: arq-eng
      name: MTEB Tatoeba (arq-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 24.98790634904795
    task:
      type: BitextMining
  - dataset:
      config: kab-eng
      name: MTEB Tatoeba (kab-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 17.19218192918193
    task:
      type: BitextMining
  - dataset:
      config: fra-eng
      name: MTEB Tatoeba (fra-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 93.26666666666667
    task:
      type: BitextMining
  - dataset:
      config: por-eng
      name: MTEB Tatoeba (por-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 94.57333333333334
    task:
      type: BitextMining
  - dataset:
      config: tat-eng
      name: MTEB Tatoeba (tat-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 42.35127206127206
    task:
      type: BitextMining
  - dataset:
      config: oci-eng
      name: MTEB Tatoeba (oci-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 51.12318903318903
    task:
      type: BitextMining
  - dataset:
      config: pol-eng
      name: MTEB Tatoeba (pol-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 94.89999999999999
    task:
      type: BitextMining
  - dataset:
      config: war-eng
      name: MTEB Tatoeba (war-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 23.856320290390055
    task:
      type: BitextMining
  - dataset:
      config: aze-eng
      name: MTEB Tatoeba (aze-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 79.52833333333334
    task:
      type: BitextMining
  - dataset:
      config: vie-eng
      name: MTEB Tatoeba (vie-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 95.93333333333334
    task:
      type: BitextMining
  - dataset:
      config: nno-eng
      name: MTEB Tatoeba (nno-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 90.75333333333333
    task:
      type: BitextMining
  - dataset:
      config: cha-eng
      name: MTEB Tatoeba (cha-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 30.802919708029197
    task:
      type: BitextMining
  - dataset:
      config: mhr-eng
      name: MTEB Tatoeba (mhr-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 15.984076294076294
    task:
      type: BitextMining
  - dataset:
      config: dan-eng
      name: MTEB Tatoeba (dan-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.82666666666667
    task:
      type: BitextMining
  - dataset:
      config: ell-eng
      name: MTEB Tatoeba (ell-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.9
    task:
      type: BitextMining
  - dataset:
      config: amh-eng
      name: MTEB Tatoeba (amh-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 76.36054421768706
    task:
      type: BitextMining
  - dataset:
      config: pam-eng
      name: MTEB Tatoeba (pam-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 9.232711399711398
    task:
      type: BitextMining
  - dataset:
      config: hsb-eng
      name: MTEB Tatoeba (hsb-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 45.640803181175855
    task:
      type: BitextMining
  - dataset:
      config: srp-eng
      name: MTEB Tatoeba (srp-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 86.29
    task:
      type: BitextMining
  - dataset:
      config: epo-eng
      name: MTEB Tatoeba (epo-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 88.90833333333332
    task:
      type: BitextMining
  - dataset:
      config: kzj-eng
      name: MTEB Tatoeba (kzj-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 11.11880248978075
    task:
      type: BitextMining
  - dataset:
      config: awa-eng
      name: MTEB Tatoeba (awa-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 48.45839345839346
    task:
      type: BitextMining
  - dataset:
      config: fao-eng
      name: MTEB Tatoeba (fao-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 65.68157033805888
    task:
      type: BitextMining
  - dataset:
      config: mal-eng
      name: MTEB Tatoeba (mal-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 94.63852498786997
    task:
      type: BitextMining
  - dataset:
      config: ile-eng
      name: MTEB Tatoeba (ile-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 81.67904761904761
    task:
      type: BitextMining
  - dataset:
      config: bos-eng
      name: MTEB Tatoeba (bos-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 89.35969868173258
    task:
      type: BitextMining
  - dataset:
      config: cor-eng
      name: MTEB Tatoeba (cor-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 5.957229437229437
    task:
      type: BitextMining
  - dataset:
      config: cat-eng
      name: MTEB Tatoeba (cat-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 91.50333333333333
    task:
      type: BitextMining
  - dataset:
      config: eus-eng
      name: MTEB Tatoeba (eus-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 63.75498778998778
    task:
      type: BitextMining
  - dataset:
      config: yue-eng
      name: MTEB Tatoeba (yue-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 82.99190476190476
    task:
      type: BitextMining
  - dataset:
      config: swe-eng
      name: MTEB Tatoeba (swe-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 92.95
    task:
      type: BitextMining
  - dataset:
      config: dtp-eng
      name: MTEB Tatoeba (dtp-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 9.054042624042623
    task:
      type: BitextMining
  - dataset:
      config: kat-eng
      name: MTEB Tatoeba (kat-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 72.77064981488574
    task:
      type: BitextMining
  - dataset:
      config: jpn-eng
      name: MTEB Tatoeba (jpn-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 93.14
    task:
      type: BitextMining
  - dataset:
      config: csb-eng
      name: MTEB Tatoeba (csb-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 29.976786498525627
    task:
      type: BitextMining
  - dataset:
      config: xho-eng
      name: MTEB Tatoeba (xho-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 67.6525821596244
    task:
      type: BitextMining
  - dataset:
      config: orv-eng
      name: MTEB Tatoeba (orv-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 33.12964812964813
    task:
      type: BitextMining
  - dataset:
      config: ind-eng
      name: MTEB Tatoeba (ind-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 92.30666666666666
    task:
      type: BitextMining
  - dataset:
      config: tuk-eng
      name: MTEB Tatoeba (tuk-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 34.36077879427633
    task:
      type: BitextMining
  - dataset:
      config: max-eng
      name: MTEB Tatoeba (max-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 52.571845212690285
    task:
      type: BitextMining
  - dataset:
      config: swh-eng
      name: MTEB Tatoeba (swh-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 58.13107263107262
    task:
      type: BitextMining
  - dataset:
      config: hin-eng
      name: MTEB Tatoeba (hin-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 93.33333333333333
    task:
      type: BitextMining
  - dataset:
      config: dsb-eng
      name: MTEB Tatoeba (dsb-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 42.87370133925458
    task:
      type: BitextMining
  - dataset:
      config: ber-eng
      name: MTEB Tatoeba (ber-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 20.394327616827614
    task:
      type: BitextMining
  - dataset:
      config: tam-eng
      name: MTEB Tatoeba (tam-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 84.29967426710098
    task:
      type: BitextMining
  - dataset:
      config: slk-eng
      name: MTEB Tatoeba (slk-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 88.80666666666667
    task:
      type: BitextMining
  - dataset:
      config: tgl-eng
      name: MTEB Tatoeba (tgl-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 67.23062271062273
    task:
      type: BitextMining
  - dataset:
      config: ast-eng
      name: MTEB Tatoeba (ast-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 78.08398950131233
    task:
      type: BitextMining
  - dataset:
      config: mkd-eng
      name: MTEB Tatoeba (mkd-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 77.85166666666666
    task:
      type: BitextMining
  - dataset:
      config: khm-eng
      name: MTEB Tatoeba (khm-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 67.63004001231148
    task:
      type: BitextMining
  - dataset:
      config: ces-eng
      name: MTEB Tatoeba (ces-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 89.77000000000001
    task:
      type: BitextMining
  - dataset:
      config: tzl-eng
      name: MTEB Tatoeba (tzl-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 40.2654503616042
    task:
      type: BitextMining
  - dataset:
      config: urd-eng
      name: MTEB Tatoeba (urd-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 83.90333333333334
    task:
      type: BitextMining
  - dataset:
      config: ara-eng
      name: MTEB Tatoeba (ara-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 77.80666666666666
    task:
      type: BitextMining
  - dataset:
      config: kor-eng
      name: MTEB Tatoeba (kor-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 84.08
    task:
      type: BitextMining
  - dataset:
      config: yid-eng
      name: MTEB Tatoeba (yid-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 60.43098607367475
    task:
      type: BitextMining
  - dataset:
      config: fin-eng
      name: MTEB Tatoeba (fin-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 88.19333333333333
    task:
      type: BitextMining
  - dataset:
      config: tha-eng
      name: MTEB Tatoeba (tha-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 90.55352798053529
    task:
      type: BitextMining
  - dataset:
      config: wuu-eng
      name: MTEB Tatoeba (wuu-eng)
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
      split: test
      type: mteb/tatoeba-bitext-mining
    metrics:
    - type: f1
      value: 88.44999999999999
    task:
      type: BitextMining
  - dataset:
      config: default
      name: MTEB ThuNewsClusteringP2P
      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
      split: test
      type: C-MTEB/ThuNewsClusteringP2P
    metrics:
    - type: v_measure
      value: 57.25416429643288
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ThuNewsClusteringS2S
      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
      split: test
      type: C-MTEB/ThuNewsClusteringS2S
    metrics:
    - type: v_measure
      value: 56.616646560243524
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB Touche2020
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
      split: test
      type: mteb/touche2020
    metrics:
    - type: ndcg_at_10
      value: 22.819
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ToxicConversationsClassification
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
      split: test
      type: mteb/toxic_conversations_50k
    metrics:
    - type: accuracy
      value: 71.02579999999999
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TweetSentimentExtractionClassification
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
      split: test
      type: mteb/tweet_sentiment_extraction
    metrics:
    - type: accuracy
      value: 57.60045274476514
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TwentyNewsgroupsClustering
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
      split: test
      type: mteb/twentynewsgroups-clustering
    metrics:
    - type: v_measure
      value: 50.346666699466205
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB TwitterSemEval2015
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
      split: test
      type: mteb/twittersemeval2015-pairclassification
    metrics:
    - type: cos_sim_ap
      value: 71.88199004440489
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB TwitterURLCorpus
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
      split: test
      type: mteb/twitterurlcorpus-pairclassification
    metrics:
    - type: cos_sim_ap
      value: 85.41587779677383
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB VideoRetrieval
      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
      split: dev
      type: C-MTEB/VideoRetrieval
    metrics:
    - type: ndcg_at_10
      value: 72.792
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB Waimai
      revision: 339287def212450dcaa9df8c22bf93e9980c7023
      split: test
      type: C-MTEB/waimai-classification
    metrics:
    - type: accuracy
      value: 82.58000000000001
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB XPQARetrieval (fr)
      revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
      split: test
      type: jinaai/xpqa
    metrics:
    - type: ndcg_at_10
      value: 67.327
    task:
      type: Retrieval
tags:
- mteb
- multilingual
- sentence-similarity
- onnx
- teradata
---

 
***See Disclaimer below***

----


# A Teradata Vantage compatible Embeddings Model

# Alibaba-NLP/gte-multilingual-base

## Overview of this Model

An Embedding Model which maps text (sentence/ paragraphs) into a vector.  The [Alibaba-NLP/gte-multilingual-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-base) model well known for its effectiveness in capturing semantic meanings in text data. It's a state-of-the-art model trained on a large corpus, capable of generating high-quality text embeddings.

- 305.37M params (Sizes in ONNX format - "fp32": 1197.36MB, "int8": 324.17MB, "uint8": 324.17MB)
- 8192 maximum input tokens 
- 768 dimensions of output vector
- Licence: apache-2.0. The released models can be used for commercial purposes free of charge.
- Reference to Original Model: https://huggingface.co/Alibaba-NLP/gte-multilingual-base


## Quickstart: Deploying this Model in Teradata Vantage

We have pre-converted the model into the ONNX format compatible with BYOM 6.0, eliminating the need for manual conversion. 

**Note:** Ensure you have access to a Teradata Database with BYOM 6.0 installed.

To get started, clone the pre-converted model directly from the Teradata HuggingFace repository.


```python

import teradataml as tdml
import getpass
from huggingface_hub import hf_hub_download

model_name = "gte-multilingual-base"
number_dimensions_output = 768
model_file_name = "model.onnx"

# Step 1: Download Model from Teradata HuggingFace Page

hf_hub_download(repo_id=f"Teradata/{model_name}", filename=f"onnx/{model_file_name}", local_dir="./")
hf_hub_download(repo_id=f"Teradata/{model_name}", filename=f"tokenizer.json", local_dir="./")

# Step 2: Create Connection to Vantage

tdml.create_context(host = input('enter your hostname'), 
                    username=input('enter your username'), 
                    password = getpass.getpass("enter your password"))

# Step 3: Load Models into Vantage
# a) Embedding model
tdml.save_byom(model_id = model_name, # must be unique in the models table
               model_file = f"onnx/{model_file_name}",
               table_name = 'embeddings_models' )
# b) Tokenizer
tdml.save_byom(model_id = model_name, # must be unique in the models table
              model_file = 'tokenizer.json',
              table_name = 'embeddings_tokenizers') 

# Step 4: Test ONNXEmbeddings Function
# Note that ONNXEmbeddings expects the 'payload' column to be 'txt'. 
# If it has got a different name, just rename it in a subquery/CTE.
input_table = "emails.emails"
embeddings_query = f"""
SELECT 
        *
from mldb.ONNXEmbeddings(
        on {input_table} as InputTable
        on (select * from embeddings_models where model_id = '{model_name}') as ModelTable DIMENSION
        on (select model as tokenizer from embeddings_tokenizers where model_id = '{model_name}') as TokenizerTable DIMENSION
        using
            Accumulate('id', 'txt') 
            ModelOutputTensor('sentence_embedding')
            EnableMemoryCheck('false')
            OutputFormat('FLOAT32({number_dimensions_output})')
            OverwriteCachedModel('true')
    ) a 
"""
DF_embeddings = tdml.DataFrame.from_query(embeddings_query)
DF_embeddings
```



## What Can I Do with the Embeddings?

Teradata Vantage includes pre-built in-database functions to process embeddings further. Explore the following examples:

- **Semantic Clustering with TD_KMeans:** [Semantic Clustering Python Notebook](https://github.com/Teradata/jupyter-demos/blob/main/UseCases/Language_Models_InVantage/Semantic_Clustering_Python.ipynb)
- **Semantic Distance with TD_VectorDistance:** [Semantic Similarity Python Notebook](https://github.com/Teradata/jupyter-demos/blob/main/UseCases/Language_Models_InVantage/Semantic_Similarity_Python.ipynb)
- **RAG-Based Application with TD_VectorDistance:** [RAG and Bedrock Query PDF Notebook](https://github.com/Teradata/jupyter-demos/blob/main/UseCases/Language_Models_InVantage/RAG_and_Bedrock_QueryPDF.ipynb)


## Deep Dive into Model Conversion to ONNX

**The steps below outline how we converted the open-source Hugging Face model into an ONNX file compatible with the in-database ONNXEmbeddings function.** 

You do not need to perform these steps—they are provided solely for documentation and transparency. However, they may be helpful if you wish to convert another model to the required format.


### Part 1. Importing and Converting Model using optimum

We start by importing the pre-trained [Alibaba-NLP/gte-multilingual-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-base) model from Hugging Face.

To enhance performance and ensure compatibility with various execution environments, we'll use the [Optimum](https://github.com/huggingface/optimum) utility to convert the model into the ONNX (Open Neural Network Exchange) format. 

After conversion to ONNX, we are fixing the opset in the ONNX file for compatibility with ONNX runtime used in Teradata Vantage

We are generating ONNX files for multiple different precisions: fp32, int8, uint8

You can find the detailed conversion steps in the file [convert.py](./convert.py)

### Part 2. Running the model in Python with onnxruntime & compare results

Once the fixes are applied, we proceed to test the correctness of the ONNX model by calculating cosine similarity between two texts using native SentenceTransformers and ONNX runtime, comparing the results.

If the results are identical, it confirms that the ONNX model gives the same result as the native models, validating its correctness and suitability for further use in the database.


```python
import onnxruntime as rt

from sentence_transformers.util import cos_sim
from sentence_transformers import SentenceTransformer

import transformers


sentences_1 = 'How is the weather today?'
sentences_2 = 'What is the current weather like today?'

# Calculate ONNX result
tokenizer = transformers.AutoTokenizer.from_pretrained("Alibaba-NLP/gte-multilingual-base")
predef_sess = rt.InferenceSession("onnx/model.onnx")

enc1 = tokenizer(sentences_1)
embeddings_1_onnx = predef_sess.run(None,     {"input_ids": [enc1.input_ids], 
     "attention_mask": [enc1.attention_mask]})

enc2 = tokenizer(sentences_2)
embeddings_2_onnx = predef_sess.run(None,     {"input_ids": [enc2.input_ids], 
     "attention_mask": [enc2.attention_mask]})


# Calculate embeddings with SentenceTransformer
model = SentenceTransformer(model_id, trust_remote_code=True)
embeddings_1_sentence_transformer = model.encode(sentences_1, normalize_embeddings=True, trust_remote_code=True)
embeddings_2_sentence_transformer = model.encode(sentences_2, normalize_embeddings=True, trust_remote_code=True)

# Compare results
print("Cosine similiarity for embeddings calculated with ONNX:" + str(cos_sim(embeddings_1_onnx[1][0], embeddings_2_onnx[1][0])))
print("Cosine similiarity for embeddings calculated with SentenceTransformer:" + str(cos_sim(embeddings_1_sentence_transformer, embeddings_2_sentence_transformer)))
```

You can find the detailed ONNX vs. SentenceTransformer result comparison steps in the file [test_local.py](./test_local.py)



-----

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