sentence-transformers safetensors qwen2 feature-extraction sentence-similarity mteb arxiv:2501.01028 license:mit model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
license: mit
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: KaLM-Embedding
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 74.16041979010495
    - type: ap
      value: 22.731316107205824
    - type: ap_weighted
      value: 22.731316107205824
    - type: f1
      value: 61.311184650259634
    - type: f1_weighted
      value: 78.92070802470501
    - type: main_score
      value: 74.16041979010495
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.35820895522387
    - type: ap
      value: 34.13026440006763
    - type: ap_weighted
      value: 34.13026440006763
    - type: f1
      value: 65.91101941691169
    - type: f1_weighted
      value: 74.90947851184335
    - type: main_score
      value: 72.35820895522387
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 95.2693
    - type: ap
      value: 93.69278757537118
    - type: ap_weighted
      value: 93.69278757537118
    - type: f1
      value: 95.26705627226383
    - type: f1_weighted
      value: 95.26705627226384
    - type: main_score
      value: 95.2693
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 51.01
    - type: f1
      value: 48.69903082137716
    - type: f1_weighted
      value: 48.69903082137716
    - type: main_score
      value: 51.01
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
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    - type: map_at_100
      value: 48.418
    - type: map_at_1000
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    - type: map_at_20
      value: 48.274
    - type: map_at_3
      value: 42.568
    - type: map_at_5
      value: 45.473
    - type: mrr_at_1
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    - type: mrr_at_10
      value: 47.80803359750735
    - type: mrr_at_100
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    - type: mrr_at_1000
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    - type: mrr_at_20
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    - type: mrr_at_3
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    - type: ndcg_at_1000
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    - type: precision_at_1
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    - type: precision_at_1000
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    - type: recall_at_1
      value: 31.436999999999998
    - type: recall_at_10
      value: 85.775
    - type: recall_at_100
      value: 99.21799999999999
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_20
      value: 94.595
    - type: recall_at_3
      value: 56.97
    - type: recall_at_5
      value: 69.70100000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: main_score
      value: 47.077382303485514
    - type: v_measure
      value: 47.077382303485514
    - type: v_measure_std
      value: 14.00039477846898
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: main_score
      value: 39.11589804504639
    - type: v_measure
      value: 39.11589804504639
    - type: v_measure_std
      value: 14.697039096668583
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: main_score
      value: 60.01096720382656
    - type: map
      value: 60.01096720382656
    - type: mrr
      value: 74.4235588972431
    - type: nAUC_map_diff1
      value: 14.296647950054817
    - type: nAUC_map_max
      value: 21.720215707737303
    - type: nAUC_map_std
      value: 18.20845510591147
    - type: nAUC_mrr_diff1
      value: 23.769639422872142
    - type: nAUC_mrr_max
      value: 33.07785201075024
    - type: nAUC_mrr_std
      value: 18.461570711690968
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
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      value: 87.60987223075549
    - type: cosine_spearman
      value: 86.23750714877664
    - type: euclidean_pearson
      value: 86.21541799525612
    - type: euclidean_spearman
      value: 86.23750714877664
    - type: main_score
      value: 86.23750714877664
    - type: manhattan_pearson
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    - type: manhattan_spearman
      value: 86.37365482930716
    - type: pearson
      value: 87.60987223075549
    - type: spearman
      value: 86.23750714877664
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
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      value: 79.16883116883118
    - type: f1
      value: 78.34840435712427
    - type: f1_weighted
      value: 78.3484043571243
    - type: main_score
      value: 79.16883116883118
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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      value: 39.29881417268574
    - type: v_measure
      value: 39.29881417268574
    - type: v_measure_std
      value: 1.1874002185778423
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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      value: 33.9614529554878
    - type: v_measure
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  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
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  - task:
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  - task:
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  - task:
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      type: mteb/imdb
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      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
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  - task:
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    dataset:
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      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
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    - type: f1
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
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    - type: f1
      value: 43.12730019766516
    - type: f1_weighted
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    - type: main_score
      value: 62.08162334701323
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
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  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
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  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
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      value: 33.84359193475579
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  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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      value: 32.43240060668634
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  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    metrics:
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  - task:
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    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
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      value: 12.154
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  - task:
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  - task:
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  - task:
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  - task:
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  - task:
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    - type: pearson
      value: 84.36926725932263
    - type: spearman
      value: 79.92986896006748
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cosine_pearson
      value: 85.34145297379273
    - type: cosine_spearman
      value: 76.66847347731301
    - type: euclidean_pearson
      value: 81.43408805079034
    - type: euclidean_spearman
      value: 76.6680945379484
    - type: main_score
      value: 76.66847347731301
    - type: manhattan_pearson
      value: 81.69812210080966
    - type: manhattan_spearman
      value: 77.00962684551284
    - type: pearson
      value: 85.34145297379273
    - type: spearman
      value: 76.66847347731301
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cosine_pearson
      value: 84.5234167909779
    - type: cosine_spearman
      value: 84.86841413445535
    - type: euclidean_pearson
      value: 84.17741655183796
    - type: euclidean_spearman
      value: 84.86841405901674
    - type: main_score
      value: 84.86841413445535
    - type: manhattan_pearson
      value: 84.15491829147086
    - type: manhattan_spearman
      value: 84.93066841323679
    - type: pearson
      value: 84.5234167909779
    - type: spearman
      value: 84.86841413445535
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cosine_pearson
      value: 83.42559938022957
    - type: cosine_spearman
      value: 80.10636060670153
    - type: euclidean_pearson
      value: 82.31695543050009
    - type: euclidean_spearman
      value: 80.10637586616073
    - type: main_score
      value: 80.10636060670153
    - type: manhattan_pearson
      value: 82.15731596876633
    - type: manhattan_spearman
      value: 80.02499151302123
    - type: pearson
      value: 83.42559938022957
    - type: spearman
      value: 80.10636060670153
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cosine_pearson
      value: 87.98708135949613
    - type: cosine_spearman
      value: 88.69670049389599
    - type: euclidean_pearson
      value: 87.73091071499016
    - type: euclidean_spearman
      value: 88.69669966606001
    - type: main_score
      value: 88.69670049389599
    - type: manhattan_pearson
      value: 87.52276751048582
    - type: manhattan_spearman
      value: 88.5214230554986
    - type: pearson
      value: 87.98708135949613
    - type: spearman
      value: 88.69670049389599
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cosine_pearson
      value: 83.38330950325803
    - type: cosine_spearman
      value: 84.62194600310691
    - type: euclidean_pearson
      value: 83.4921014845454
    - type: euclidean_spearman
      value: 84.62194539439683
    - type: main_score
      value: 84.62194600310691
    - type: manhattan_pearson
      value: 83.27754689500482
    - type: manhattan_spearman
      value: 84.37797144965002
    - type: pearson
      value: 83.38330950325803
    - type: spearman
      value: 84.62194600310691
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 64.3970938916265
    - type: cosine_spearman
      value: 64.20857293171593
    - type: euclidean_pearson
      value: 64.70484646950464
    - type: euclidean_spearman
      value: 64.20857293171593
    - type: main_score
      value: 64.20857293171593
    - type: manhattan_pearson
      value: 63.61585574374933
    - type: manhattan_spearman
      value: 62.52898030084564
    - type: pearson
      value: 64.3970938916265
    - type: spearman
      value: 64.20857293171593
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 78.3035787778662
    - type: cosine_spearman
      value: 78.85326338385796
    - type: euclidean_pearson
      value: 78.59090666313418
    - type: euclidean_spearman
      value: 78.85326338385796
    - type: main_score
      value: 78.85326338385796
    - type: manhattan_pearson
      value: 78.4961035895383
    - type: manhattan_spearman
      value: 78.42104373908565
    - type: pearson
      value: 78.3035787778662
    - type: spearman
      value: 78.85326338385796
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 88.20922919233338
    - type: cosine_spearman
      value: 87.94347302365394
    - type: euclidean_pearson
      value: 87.98965741145625
    - type: euclidean_spearman
      value: 87.94347302365394
    - type: main_score
      value: 87.94347302365394
    - type: manhattan_pearson
      value: 87.94636580768939
    - type: manhattan_spearman
      value: 87.82077364455115
    - type: pearson
      value: 88.20922919233338
    - type: spearman
      value: 87.94347302365394
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 58.50589296592958
    - type: cosine_spearman
      value: 57.045627811103
    - type: euclidean_pearson
      value: 58.54066429107441
    - type: euclidean_spearman
      value: 57.045627811103
    - type: main_score
      value: 57.045627811103
    - type: manhattan_pearson
      value: 57.77923152721202
    - type: manhattan_spearman
      value: 55.832507020505886
    - type: pearson
      value: 58.50589296592958
    - type: spearman
      value: 57.045627811103
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 79.01593420315352
    - type: cosine_spearman
      value: 79.86309144376173
    - type: euclidean_pearson
      value: 78.85136309334905
    - type: euclidean_spearman
      value: 79.86309144376173
    - type: main_score
      value: 79.86309144376173
    - type: manhattan_pearson
      value: 78.87419337945624
    - type: manhattan_spearman
      value: 80.0980944874198
    - type: pearson
      value: 79.01593420315352
    - type: spearman
      value: 79.86309144376173
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 79.67432399995894
    - type: cosine_spearman
      value: 79.12303288340163
    - type: euclidean_pearson
      value: 79.721668775324
    - type: euclidean_spearman
      value: 79.12303288340163
    - type: main_score
      value: 79.12303288340163
    - type: manhattan_pearson
      value: 79.33800466555394
    - type: manhattan_spearman
      value: 78.30603645374914
    - type: pearson
      value: 79.67432399995894
    - type: spearman
      value: 79.12303288340163
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 78.92024449526863
    - type: cosine_spearman
      value: 79.06471992660374
    - type: euclidean_pearson
      value: 78.85388657114522
    - type: euclidean_spearman
      value: 79.06471992660374
    - type: main_score
      value: 79.06471992660374
    - type: manhattan_pearson
      value: 78.56658857806735
    - type: manhattan_spearman
      value: 78.5908742980949
    - type: pearson
      value: 78.92024449526863
    - type: spearman
      value: 79.06471992660374
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 76.64708509569135
    - type: cosine_spearman
      value: 75.76775070804274
    - type: euclidean_pearson
      value: 76.69358579979829
    - type: euclidean_spearman
      value: 75.76775070804274
    - type: main_score
      value: 75.76775070804274
    - type: manhattan_pearson
      value: 76.28750520391006
    - type: manhattan_spearman
      value: 75.30493726054976
    - type: pearson
      value: 76.64708509569135
    - type: spearman
      value: 75.76775070804274
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 69.07403446182418
    - type: cosine_spearman
      value: 68.99668192503603
    - type: euclidean_pearson
      value: 70.82685591260719
    - type: euclidean_spearman
      value: 68.99668192503603
    - type: main_score
      value: 68.99668192503603
    - type: manhattan_pearson
      value: 70.94201332797343
    - type: manhattan_spearman
      value: 68.98821773218067
    - type: pearson
      value: 69.07403446182418
    - type: spearman
      value: 68.99668192503603
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 65.95032307094047
    - type: cosine_spearman
      value: 63.15571038787516
    - type: euclidean_pearson
      value: 68.31815956207403
    - type: euclidean_spearman
      value: 63.15571038787516
    - type: main_score
      value: 63.15571038787516
    - type: manhattan_pearson
      value: 69.57471678363024
    - type: manhattan_spearman
      value: 63.78770917466211
    - type: pearson
      value: 65.95032307094047
    - type: spearman
      value: 63.15571038787516
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 76.57985370197574
    - type: cosine_spearman
      value: 78.61171041249278
    - type: euclidean_pearson
      value: 77.64916374513423
    - type: euclidean_spearman
      value: 78.61182871621082
    - type: main_score
      value: 78.61171041249278
    - type: manhattan_pearson
      value: 79.45516154600577
    - type: manhattan_spearman
      value: 79.81770224017768
    - type: pearson
      value: 76.57985370197574
    - type: spearman
      value: 78.61171041249278
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 78.66979183071325
    - type: cosine_spearman
      value: 76.74899167835852
    - type: euclidean_pearson
      value: 78.89780095637012
    - type: euclidean_spearman
      value: 76.74899167835852
    - type: main_score
      value: 76.74899167835852
    - type: manhattan_pearson
      value: 79.18536398264527
    - type: manhattan_spearman
      value: 77.8533686712189
    - type: pearson
      value: 78.66979183071325
    - type: spearman
      value: 76.74899167835852
    - type: cosine_pearson
      value: 78.67129157333113
    - type: cosine_spearman
      value: 77.17497249706467
    - type: euclidean_pearson
      value: 78.93527680834069
    - type: euclidean_spearman
      value: 77.17497249706467
    - type: main_score
      value: 77.17497249706467
    - type: manhattan_pearson
      value: 79.17117078125075
    - type: manhattan_spearman
      value: 77.98920639910075
    - type: pearson
      value: 78.67129157333113
    - type: spearman
      value: 77.17497249706467
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 75.65018415517595
    - type: cosine_spearman
      value: 74.96983110528109
    - type: euclidean_pearson
      value: 77.0199252096022
    - type: euclidean_spearman
      value: 75.05313744822759
    - type: main_score
      value: 74.96983110528109
    - type: manhattan_pearson
      value: 77.28747618528581
    - type: manhattan_spearman
      value: 74.95188542213391
    - type: pearson
      value: 75.65018415517595
    - type: spearman
      value: 74.96983110528109
    - type: cosine_pearson
      value: 75.65018415517595
    - type: cosine_spearman
      value: 74.96983110528109
    - type: euclidean_pearson
      value: 77.0199252096022
    - type: euclidean_spearman
      value: 75.05313744822759
    - type: main_score
      value: 74.96983110528109
    - type: manhattan_pearson
      value: 77.28747618528581
    - type: manhattan_spearman
      value: 74.95188542213391
    - type: pearson
      value: 75.65018415517595
    - type: spearman
      value: 74.96983110528109
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cosine_pearson
      value: 84.89952732150343
    - type: cosine_spearman
      value: 86.06896054399277
    - type: euclidean_pearson
      value: 85.69195853460913
    - type: euclidean_spearman
      value: 86.06896054399277
    - type: main_score
      value: 86.06896054399277
    - type: manhattan_pearson
      value: 85.56550688049849
    - type: manhattan_spearman
      value: 85.96422284827248
    - type: pearson
      value: 84.89952732150343
    - type: spearman
      value: 86.06896054399277
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: main_score
      value: 81.89447973144247
    - type: map
      value: 81.89447973144247
    - type: mrr
      value: 95.02511830943203
    - type: nAUC_map_diff1
      value: 3.3432260393863147
    - type: nAUC_map_max
      value: 54.252667154593915
    - type: nAUC_map_std
      value: 68.86046114121041
    - type: nAUC_mrr_diff1
      value: 48.53496653582678
    - type: nAUC_mrr_max
      value: 85.71793394587537
    - type: nAUC_mrr_std
      value: 80.13736591117815
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: main_score
      value: 73.055
    - type: map_at_1
      value: 57.760999999999996
    - type: map_at_10
      value: 68.73700000000001
    - type: map_at_100
      value: 69.248
    - type: map_at_1000
      value: 69.271
    - type: map_at_20
      value: 69.059
    - type: map_at_3
      value: 66.235
    - type: map_at_5
      value: 67.843
    - type: mrr_at_1
      value: 60.66666666666667
    - type: mrr_at_10
      value: 69.7063492063492
    - type: mrr_at_100
      value: 70.13874332314896
    - type: mrr_at_1000
      value: 70.16105806682286
    - type: mrr_at_20
      value: 69.97925265738732
    - type: mrr_at_3
      value: 68.0
    - type: mrr_at_5
      value: 69.16666666666667
    - type: nauc_map_at_1000_diff1
      value: 70.43790903123511
    - type: nauc_map_at_1000_max
      value: 54.58438799194478
    - type: nauc_map_at_1000_std
      value: -2.3233833924225875
    - type: nauc_map_at_100_diff1
      value: 70.43647328927425
    - type: nauc_map_at_100_max
      value: 54.60393233697298
    - type: nauc_map_at_100_std
      value: -2.296496281894915
    - type: nauc_map_at_10_diff1
      value: 70.36871958614046
    - type: nauc_map_at_10_max
      value: 54.67011099551128
    - type: nauc_map_at_10_std
      value: -2.7009625352656426
    - type: nauc_map_at_1_diff1
      value: 74.99352374397856
    - type: nauc_map_at_1_max
      value: 50.00344836993502
    - type: nauc_map_at_1_std
      value: -8.698012201837718
    - type: nauc_map_at_20_diff1
      value: 70.28211747093155
    - type: nauc_map_at_20_max
      value: 54.553120080500996
    - type: nauc_map_at_20_std
      value: -2.5857819931480246
    - type: nauc_map_at_3_diff1
      value: 71.42267536616798
    - type: nauc_map_at_3_max
      value: 54.14853872152404
    - type: nauc_map_at_3_std
      value: -3.3672073293896654
    - type: nauc_map_at_5_diff1
      value: 70.5522364898511
    - type: nauc_map_at_5_max
      value: 53.82183956625946
    - type: nauc_map_at_5_std
      value: -3.8112884869905086
    - type: nauc_mrr_at_1000_diff1
      value: 70.31304494231345
    - type: nauc_mrr_at_1000_max
      value: 55.634864405262206
    - type: nauc_mrr_at_1000_std
      value: -0.9073602724006471
    - type: nauc_mrr_at_100_diff1
      value: 70.31169722312256
    - type: nauc_mrr_at_100_max
      value: 55.653794547616464
    - type: nauc_mrr_at_100_std
      value: -0.8812919296154862
    - type: nauc_mrr_at_10_diff1
      value: 70.20728957800745
    - type: nauc_mrr_at_10_max
      value: 55.82409315449895
    - type: nauc_mrr_at_10_std
      value: -1.075930464035488
    - type: nauc_mrr_at_1_diff1
      value: 74.42858144028513
    - type: nauc_mrr_at_1_max
      value: 54.28150936595816
    - type: nauc_mrr_at_1_std
      value: -2.2125887288127233
    - type: nauc_mrr_at_20_diff1
      value: 70.12751951178618
    - type: nauc_mrr_at_20_max
      value: 55.646395586345186
    - type: nauc_mrr_at_20_std
      value: -1.0679937201638918
    - type: nauc_mrr_at_3_diff1
      value: 70.83694438588687
    - type: nauc_mrr_at_3_max
      value: 56.13927732102838
    - type: nauc_mrr_at_3_std
      value: -0.7791089874218045
    - type: nauc_mrr_at_5_diff1
      value: 70.10204767208957
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    - type: precision_at_1
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    - type: precision_at_10
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    - type: recall_at_1
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    - type: recall_at_20
      value: 89.22200000000001
    - type: recall_at_3
      value: 74.933
    - type: recall_at_5
      value: 80.511
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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    - type: cosine_ap
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    - type: cosine_precision
      value: 90.33232628398792
    - type: cosine_recall
      value: 89.7
    - type: dot_accuracy
      value: 99.8029702970297
    - type: dot_accuracy_threshold
      value: 74.40159320831299
    - type: dot_ap
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    - type: dot_f1
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    - type: dot_f1_threshold
      value: 74.40159320831299
    - type: dot_precision
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    - type: dot_recall
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    - type: euclidean_accuracy
      value: 99.8029702970297
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    - type: euclidean_ap
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    - type: euclidean_precision
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    - type: euclidean_recall
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    - type: main_score
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    - type: manhattan_accuracy
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    - type: manhattan_f1_threshold
      value: 1696.7340469360352
    - type: manhattan_precision
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    - type: manhattan_recall
      value: 90.9
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    - type: max_f1
      value: 90.4927824788452
    - type: max_precision
      value: 90.33232628398792
    - type: max_recall
      value: 90.9
    - type: similarity_accuracy
      value: 99.8029702970297
    - type: similarity_accuracy_threshold
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    - type: similarity_ap
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    - type: similarity_f1_threshold
      value: 74.40159320831299
    - type: similarity_precision
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    - type: similarity_recall
      value: 89.7
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
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      value: 67.22104632684339
    - type: v_measure
      value: 67.22104632684339
    - type: v_measure_std
      value: 4.510073189377009
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
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      value: 33.69502959609247
    - type: v_measure
      value: 33.69502959609247
    - type: v_measure_std
      value: 1.7351941868223697
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
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    - type: map
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  - task:
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    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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    - type: dot_pearson
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    - type: pearson
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    - type: spearman
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  - task:
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      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
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    - type: precision_at_20
      value: 80.30000000000001
    - type: precision_at_3
      value: 86.667
    - type: precision_at_5
      value: 86.4
    - type: recall_at_1
      value: 0.22100000000000003
    - type: recall_at_10
      value: 2.179
    - type: recall_at_100
      value: 15.934000000000001
    - type: recall_at_1000
      value: 54.458
    - type: recall_at_20
      value: 4.144
    - type: recall_at_3
      value: 0.6859999999999999
    - type: recall_at_5
      value: 1.1320000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: main_score
      value: 28.907
    - type: map_at_1
      value: 2.675
    - type: map_at_10
      value: 12.215
    - type: map_at_100
      value: 18.7
    - type: map_at_1000
      value: 20.398
    - type: map_at_20
      value: 15.078
    - type: map_at_3
      value: 6.241
    - type: map_at_5
      value: 8.289
    - type: mrr_at_1
      value: 32.6530612244898
    - type: mrr_at_10
      value: 50.01133786848071
    - type: mrr_at_100
      value: 50.77517365675259
    - type: mrr_at_1000
      value: 50.77517365675259
    - type: mrr_at_20
      value: 50.588814902724664
    - type: mrr_at_3
      value: 45.578231292517
    - type: mrr_at_5
      value: 48.53741496598638
    - type: nauc_map_at_1000_diff1
      value: -5.684538294981354
    - type: nauc_map_at_1000_max
      value: -33.46305720843361
    - type: nauc_map_at_1000_std
      value: 1.9671166101260358
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      value: -3.9527668773790374
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      value: -33.547343271958304
    - type: nauc_map_at_100_std
      value: -1.4543726200894687
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      value: -3.6912102827982975
    - type: nauc_map_at_10_max
      value: -37.051501400243644
    - type: nauc_map_at_10_std
      value: -18.58369649223091
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      value: 8.542642521750217
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      value: -42.118453460843014
    - type: nauc_map_at_1_std
      value: -21.4477651608444
    - type: nauc_map_at_20_diff1
      value: -4.1294483682157335
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      value: -32.055300714683774
    - type: nauc_map_at_20_std
      value: -13.633460827906779
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      value: 4.166012812499575
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      value: -44.421760913346375
    - type: nauc_map_at_3_std
      value: -22.934729762627693
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      value: 5.0705280599427285
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      value: -39.880207516910055
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      value: -19.089070592204358
    - type: nauc_mrr_at_1000_diff1
      value: 8.136502099178854
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      value: -54.053135657703564
    - type: nauc_mrr_at_1000_std
      value: 0.8410793475356224
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      value: 8.136502099178854
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      value: -54.053135657703564
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      value: 0.8410793475356224
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      value: 7.021058071372796
    - type: nauc_mrr_at_10_max
      value: -55.576671480124475
    - type: nauc_mrr_at_10_std
      value: 2.659844175871393
    - type: nauc_mrr_at_1_diff1
      value: 21.763874961879942
    - type: nauc_mrr_at_1_max
      value: -42.10185605661237
    - type: nauc_mrr_at_1_std
      value: -6.492292167140558
    - type: nauc_mrr_at_20_diff1
      value: 8.441891181402887
    - type: nauc_mrr_at_20_max
      value: -54.466795585812235
    - type: nauc_mrr_at_20_std
      value: 0.916114699709143
    - type: nauc_mrr_at_3_diff1
      value: 7.551389256661414
    - type: nauc_mrr_at_3_max
      value: -46.97364074837694
    - type: nauc_mrr_at_3_std
      value: 1.0411397370775466
    - type: nauc_mrr_at_5_diff1
      value: 5.235804734715955
    - type: nauc_mrr_at_5_max
      value: -54.37509495435838
    - type: nauc_mrr_at_5_std
      value: 2.779654633655762
    - type: nauc_ndcg_at_1000_diff1
      value: -15.397449719696779
    - type: nauc_ndcg_at_1000_max
      value: -43.619552110596665
    - type: nauc_ndcg_at_1000_std
      value: 26.3557588044005
    - type: nauc_ndcg_at_100_diff1
      value: -8.064551008407328
    - type: nauc_ndcg_at_100_max
      value: -45.62898014606384
    - type: nauc_ndcg_at_100_std
      value: 19.02252139372526
    - type: nauc_ndcg_at_10_diff1
      value: -4.128778098656938
    - type: nauc_ndcg_at_10_max
      value: -47.533595647961825
    - type: nauc_ndcg_at_10_std
      value: -3.3387983790901616
    - type: nauc_ndcg_at_1_diff1
      value: 15.241311807512584
    - type: nauc_ndcg_at_1_max
      value: -41.98413041761103
    - type: nauc_ndcg_at_1_std
      value: -1.7966111564973624
    - type: nauc_ndcg_at_20_diff1
      value: -5.70487127711277
    - type: nauc_ndcg_at_20_max
      value: -43.296928773082485
    - type: nauc_ndcg_at_20_std
      value: -4.953768651191041
    - type: nauc_ndcg_at_3_diff1
      value: 10.059341497787937
    - type: nauc_ndcg_at_3_max
      value: -40.68501908879975
    - type: nauc_ndcg_at_3_std
      value: -3.6931074797187877
    - type: nauc_ndcg_at_5_diff1
      value: 7.526983752941929
    - type: nauc_ndcg_at_5_max
      value: -43.365397576700275
    - type: nauc_ndcg_at_5_std
      value: 0.32616836825174683
    - type: nauc_precision_at_1000_diff1
      value: -7.438317571660842
    - type: nauc_precision_at_1000_max
      value: 34.73241001748508
    - type: nauc_precision_at_1000_std
      value: 36.25365158109604
    - type: nauc_precision_at_100_diff1
      value: -4.627005077446657
    - type: nauc_precision_at_100_max
      value: -15.93628289282409
    - type: nauc_precision_at_100_std
      value: 68.61386525027707
    - type: nauc_precision_at_10_diff1
      value: -10.52039936457346
    - type: nauc_precision_at_10_max
      value: -43.34615042118174
    - type: nauc_precision_at_10_std
      value: 9.318534549691767
    - type: nauc_precision_at_1_diff1
      value: 21.763874961879942
    - type: nauc_precision_at_1_max
      value: -42.10185605661237
    - type: nauc_precision_at_1_std
      value: -6.492292167140558
    - type: nauc_precision_at_20_diff1
      value: -2.287812706503246
    - type: nauc_precision_at_20_max
      value: -28.10959274429549
    - type: nauc_precision_at_20_std
      value: 16.788667831779485
    - type: nauc_precision_at_3_diff1
      value: 11.569650243424755
    - type: nauc_precision_at_3_max
      value: -41.668998559185844
    - type: nauc_precision_at_3_std
      value: -0.3803285872339615
    - type: nauc_precision_at_5_diff1
      value: 7.598490650206377
    - type: nauc_precision_at_5_max
      value: -41.68148813885381
    - type: nauc_precision_at_5_std
      value: 7.354258555131649
    - type: nauc_recall_at_1000_diff1
      value: -50.220542196994636
    - type: nauc_recall_at_1000_max
      value: -16.95193388500635
    - type: nauc_recall_at_1000_std
      value: 69.28134193017735
    - type: nauc_recall_at_100_diff1
      value: -15.415419361213853
    - type: nauc_recall_at_100_max
      value: -33.60910097372997
    - type: nauc_recall_at_100_std
      value: 35.403748730364256
    - type: nauc_recall_at_10_diff1
      value: -14.144822663337028
    - type: nauc_recall_at_10_max
      value: -38.11986778901871
    - type: nauc_recall_at_10_std
      value: -13.87707926888663
    - type: nauc_recall_at_1_diff1
      value: 8.542642521750217
    - type: nauc_recall_at_1_max
      value: -42.118453460843014
    - type: nauc_recall_at_1_std
      value: -21.4477651608444
    - type: nauc_recall_at_20_diff1
      value: -12.3394417307943
    - type: nauc_recall_at_20_max
      value: -32.75019884128939
    - type: nauc_recall_at_20_std
      value: -6.875770812126497
    - type: nauc_recall_at_3_diff1
      value: -0.907011119452535
    - type: nauc_recall_at_3_max
      value: -42.06461204250678
    - type: nauc_recall_at_3_std
      value: -18.765470997666945
    - type: nauc_recall_at_5_diff1
      value: -1.063588562013453
    - type: nauc_recall_at_5_max
      value: -39.15779594344513
    - type: nauc_recall_at_5_std
      value: -14.839683507905466
    - type: ndcg_at_1
      value: 29.592000000000002
    - type: ndcg_at_10
      value: 28.907
    - type: ndcg_at_100
      value: 40.211000000000006
    - type: ndcg_at_1000
      value: 51.482000000000006
    - type: ndcg_at_20
      value: 29.804000000000002
    - type: ndcg_at_3
      value: 30.802000000000003
    - type: ndcg_at_5
      value: 29.511
    - type: precision_at_1
      value: 32.653
    - type: precision_at_10
      value: 26.531
    - type: precision_at_100
      value: 8.224
    - type: precision_at_1000
      value: 1.576
    - type: precision_at_20
      value: 20.102
    - type: precision_at_3
      value: 34.014
    - type: precision_at_5
      value: 30.203999999999997
    - type: recall_at_1
      value: 2.675
    - type: recall_at_10
      value: 19.750999999999998
    - type: recall_at_100
      value: 50.365
    - type: recall_at_1000
      value: 84.773
    - type: recall_at_20
      value: 27.632
    - type: recall_at_3
      value: 7.578
    - type: recall_at_5
      value: 11.346
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 70.810546875
    - type: ap
      value: 14.252152092007437
    - type: ap_weighted
      value: 14.252152092007437
    - type: f1
      value: 54.48430687519361
    - type: f1_weighted
      value: 77.28107973539473
    - type: main_score
      value: 70.810546875
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 62.66553480475382
    - type: f1
      value: 62.053566222838384
    - type: f1_weighted
      value: 60.48069640139468
    - type: main_score
      value: 62.66553480475382
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: main_score
      value: 49.676842982432774
    - type: v_measure
      value: 49.676842982432774
    - type: v_measure_std
      value: 1.3041225457855343
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cosine_accuracy
      value: 85.07480479227513
    - type: cosine_accuracy_threshold
      value: 78.39158177375793
    - type: cosine_ap
      value: 70.92737526837412
    - type: cosine_f1
      value: 66.1954959271682
    - type: cosine_f1_threshold
      value: 74.12481307983398
    - type: cosine_precision
      value: 60.61869240895129
    - type: cosine_recall
      value: 72.9023746701847
    - type: dot_accuracy
      value: 85.07480479227513
    - type: dot_accuracy_threshold
      value: 78.39158773422241
    - type: dot_ap
      value: 70.92737601494514
    - type: dot_f1
      value: 66.1954959271682
    - type: dot_f1_threshold
      value: 74.12482500076294
    - type: dot_precision
      value: 60.61869240895129
    - type: dot_recall
      value: 72.9023746701847
    - type: euclidean_accuracy
      value: 85.07480479227513
    - type: euclidean_accuracy_threshold
      value: 65.73951244354248
    - type: euclidean_ap
      value: 70.92738137519932
    - type: euclidean_f1
      value: 66.1954959271682
    - type: euclidean_f1_threshold
      value: 71.93772792816162
    - type: euclidean_precision
      value: 60.61869240895129
    - type: euclidean_recall
      value: 72.9023746701847
    - type: main_score
      value: 70.92738137519932
    - type: manhattan_accuracy
      value: 84.89002801454372
    - type: manhattan_accuracy_threshold
      value: 1543.7227249145508
    - type: manhattan_ap
      value: 70.45819704836475
    - type: manhattan_f1
      value: 65.75607397558322
    - type: manhattan_f1_threshold
      value: 1691.067886352539
    - type: manhattan_precision
      value: 60.673656033905864
    - type: manhattan_recall
      value: 71.76781002638522
    - type: max_ap
      value: 70.92738137519932
    - type: max_f1
      value: 66.1954959271682
    - type: max_precision
      value: 60.673656033905864
    - type: max_recall
      value: 72.9023746701847
    - type: similarity_accuracy
      value: 85.07480479227513
    - type: similarity_accuracy_threshold
      value: 78.39158177375793
    - type: similarity_ap
      value: 70.92737526837412
    - type: similarity_f1
      value: 66.1954959271682
    - type: similarity_f1_threshold
      value: 74.12481307983398
    - type: similarity_precision
      value: 60.61869240895129
    - type: similarity_recall
      value: 72.9023746701847
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cosine_accuracy
      value: 89.32355338223309
    - type: cosine_accuracy_threshold
      value: 72.50972986221313
    - type: cosine_ap
      value: 86.74895762701595
    - type: cosine_f1
      value: 79.21738810635873
    - type: cosine_f1_threshold
      value: 69.94493007659912
    - type: cosine_precision
      value: 75.82905020066183
    - type: cosine_recall
      value: 82.9226978749615
    - type: dot_accuracy
      value: 89.32355338223309
    - type: dot_accuracy_threshold
      value: 72.50974178314209
    - type: dot_ap
      value: 86.74894970312789
    - type: dot_f1
      value: 79.21738810635873
    - type: dot_f1_threshold
      value: 69.94493007659912
    - type: dot_precision
      value: 75.82905020066183
    - type: dot_recall
      value: 82.9226978749615
    - type: euclidean_accuracy
      value: 89.32355338223309
    - type: euclidean_accuracy_threshold
      value: 74.14885759353638
    - type: euclidean_ap
      value: 86.74893799074754
    - type: euclidean_f1
      value: 79.21738810635873
    - type: euclidean_f1_threshold
      value: 77.53072381019592
    - type: euclidean_precision
      value: 75.82905020066183
    - type: euclidean_recall
      value: 82.9226978749615
    - type: main_score
      value: 86.74895762701595
    - type: manhattan_accuracy
      value: 89.28474405247022
    - type: manhattan_accuracy_threshold
      value: 1725.102424621582
    - type: manhattan_ap
      value: 86.69699016049593
    - type: manhattan_f1
      value: 79.00847425990219
    - type: manhattan_f1_threshold
      value: 1807.0615768432617
    - type: manhattan_precision
      value: 76.68671642872673
    - type: manhattan_recall
      value: 81.4752078842008
    - type: max_ap
      value: 86.74895762701595
    - type: max_f1
      value: 79.21738810635873
    - type: max_precision
      value: 76.68671642872673
    - type: max_recall
      value: 82.9226978749615
    - type: similarity_accuracy
      value: 89.32355338223309
    - type: similarity_accuracy_threshold
      value: 72.50972986221313
    - type: similarity_ap
      value: 86.74895762701595
    - type: similarity_f1
      value: 79.21738810635873
    - type: similarity_f1_threshold
      value: 69.94493007659912
    - type: similarity_precision
      value: 75.82905020066183
    - type: similarity_recall
      value: 82.9226978749615
  - task:
      type: STS
    dataset:
      name: MTEB AFQMC
      type: C-MTEB/AFQMC
      config: default
      split: validation
      revision: b44c3b011063adb25877c13823db83bb193913c4
    metrics:
    - type: cosine_pearson
      value: 38.29145368837485
    - type: cosine_spearman
      value: 39.41056570139273
    - type: euclidean_pearson
      value: 38.0651461534699
    - type: euclidean_spearman
      value: 39.41056569992215
    - type: main_score
      value: 39.41056570139273
    - type: manhattan_pearson
      value: 37.70876309636298
    - type: manhattan_spearman
      value: 39.04864822187025
    - type: pearson
      value: 38.29145368837485
    - type: spearman
      value: 39.41056570139273
  - task:
      type: STS
    dataset:
      name: MTEB ATEC
      type: C-MTEB/ATEC
      config: default
      split: test
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
    metrics:
    - type: cosine_pearson
      value: 46.47704725371303
    - type: cosine_spearman
      value: 46.9183608596495
    - type: euclidean_pearson
      value: 49.36420417260176
    - type: euclidean_spearman
      value: 46.91835860770197
    - type: main_score
      value: 46.9183608596495
    - type: manhattan_pearson
      value: 49.124318954541145
    - type: manhattan_spearman
      value: 46.69432997494852
    - type: pearson
      value: 46.47704725371303
    - type: spearman
      value: 46.9183608596495
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 41.858000000000004
    - type: f1
      value: 38.04731113109237
    - type: f1_weighted
      value: 38.04731113109237
    - type: main_score
      value: 41.858000000000004
  - task:
      type: STS
    dataset:
      name: MTEB BQ
      type: C-MTEB/BQ
      config: default
      split: test
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
    metrics:
    - type: cosine_pearson
      value: 51.2270285721989
    - type: cosine_spearman
      value: 51.53381532349815
    - type: euclidean_pearson
      value: 50.83672339980501
    - type: euclidean_spearman
      value: 51.53382225123762
    - type: main_score
      value: 51.53381532349815
    - type: manhattan_pearson
      value: 50.481897254555655
    - type: manhattan_spearman
      value: 51.165938122581764
    - type: pearson
      value: 51.2270285721989
    - type: spearman
      value: 51.53381532349815
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringP2P
      type: C-MTEB/CLSClusteringP2P
      config: default
      split: test
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
    metrics:
    - type: main_score
      value: 42.6351765343486
    - type: v_measure
      value: 42.6351765343486
    - type: v_measure_std
      value: 0.8266776246358534
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringS2S
      type: C-MTEB/CLSClusteringS2S
      config: default
      split: test
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
    metrics:
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      value: 39.14026434895999
    - type: v_measure
      value: 39.14026434895999
    - type: v_measure_std
      value: 0.8843326244130124
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv1
      type: C-MTEB/CMedQAv1-reranking
      config: default
      split: test
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
    metrics:
    - type: main_score
      value: 81.62649518330059
    - type: map
      value: 81.62649518330059
    - type: mrr
      value: 84.59920634920634
    - type: nAUC_map_diff1
      value: 57.57622865226385
    - type: nAUC_map_max
      value: 64.24578070815535
    - type: nAUC_map_std
      value: 25.825835637398292
    - type: nAUC_mrr_diff1
      value: 64.506555321586
    - type: nAUC_mrr_max
      value: 73.72849839805279
    - type: nAUC_mrr_std
      value: 33.50231715071016
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv2
      type: C-MTEB/CMedQAv2-reranking
      config: default
      split: test
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
    metrics:
    - type: main_score
      value: 82.6884842555647
    - type: map
      value: 82.6884842555647
    - type: mrr
      value: 85.7413492063492
    - type: nAUC_map_diff1
      value: 62.227875149480674
    - type: nAUC_map_max
      value: 65.39899447833739
    - type: nAUC_map_std
      value: 22.232770911289762
    - type: nAUC_mrr_diff1
      value: 71.02339957841794
    - type: nAUC_mrr_max
      value: 75.79106833222022
    - type: nAUC_mrr_std
      value: 31.922312297325313
  - task:
      type: Retrieval
    dataset:
      name: MTEB CmedqaRetrieval
      type: C-MTEB/CmedqaRetrieval
      config: default
      split: dev
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
    metrics:
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      value: 41.912
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      value: 24.154
    - type: map_at_10
      value: 35.771
    - type: map_at_100
      value: 37.361
    - type: map_at_1000
      value: 37.501
    - type: map_at_20
      value: 36.614000000000004
    - type: map_at_3
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    - type: map_at_5
      value: 34.135
    - type: mrr_at_1
      value: 36.959239809952486
    - type: mrr_at_10
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    - type: mrr_at_100
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    - type: mrr_at_1000
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    - type: mrr_at_20
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    - type: nauc_recall_at_5_diff1
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    - type: nauc_recall_at_5_std
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    - type: ndcg_at_1
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    - type: ndcg_at_10
      value: 41.912
    - type: ndcg_at_100
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    - type: ndcg_at_1000
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    - type: ndcg_at_20
      value: 44.237
    - type: ndcg_at_3
      value: 37.596000000000004
    - type: ndcg_at_5
      value: 39.257
    - type: precision_at_1
      value: 36.958999999999996
    - type: precision_at_10
      value: 9.222
    - type: precision_at_100
      value: 1.456
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_20
      value: 5.404
    - type: precision_at_3
      value: 21.346999999999998
    - type: precision_at_5
      value: 15.204
    - type: recall_at_1
      value: 24.154
    - type: recall_at_10
      value: 51.13799999999999
    - type: recall_at_100
      value: 78.44200000000001
    - type: recall_at_1000
      value: 96.607
    - type: recall_at_20
      value: 59.01499999999999
    - type: recall_at_3
      value: 37.645
    - type: recall_at_5
      value: 43.24
  - task:
      type: PairClassification
    dataset:
      name: MTEB Cmnli
      type: C-MTEB/CMNLI
      config: default
      split: validation
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
    metrics:
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      value: 70.24654239326519
    - type: cosine_accuracy_threshold
      value: 65.65687656402588
    - type: cosine_ap
      value: 76.97337656087815
    - type: cosine_f1
      value: 72.89293849658314
    - type: cosine_f1_threshold
      value: 58.187782764434814
    - type: cosine_precision
      value: 63.230240549828174
    - type: cosine_recall
      value: 86.04161795651157
    - type: dot_accuracy
      value: 70.24654239326519
    - type: dot_accuracy_threshold
      value: 65.65687656402588
    - type: dot_ap
      value: 76.99306253217402
    - type: dot_f1
      value: 72.89293849658314
    - type: dot_f1_threshold
      value: 58.18778872489929
    - type: dot_precision
      value: 63.230240549828174
    - type: dot_recall
      value: 86.04161795651157
    - type: euclidean_accuracy
      value: 70.24654239326519
    - type: euclidean_accuracy_threshold
      value: 82.8771710395813
    - type: euclidean_ap
      value: 76.97337656087815
    - type: euclidean_f1
      value: 72.89293849658314
    - type: euclidean_f1_threshold
      value: 91.44638776779175
    - type: euclidean_precision
      value: 63.230240549828174
    - type: euclidean_recall
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    - type: main_score
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    - type: manhattan_accuracy
      value: 69.74143114852676
    - type: manhattan_accuracy_threshold
      value: 1963.1107330322266
    - type: manhattan_ap
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    - type: manhattan_f1
      value: 72.70526528142021
    - type: manhattan_f1_threshold
      value: 2121.240234375
    - type: manhattan_precision
      value: 63.93471704807522
    - type: manhattan_recall
      value: 84.26467149871405
    - type: max_ap
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    - type: max_f1
      value: 72.89293849658314
    - type: max_precision
      value: 63.93471704807522
    - type: max_recall
      value: 86.04161795651157
    - type: similarity_accuracy
      value: 70.24654239326519
    - type: similarity_accuracy_threshold
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    - type: similarity_ap
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    - type: similarity_f1
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    - type: similarity_f1_threshold
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    - type: similarity_precision
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    - type: similarity_recall
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  - task:
      type: Retrieval
    dataset:
      name: MTEB CovidRetrieval
      type: C-MTEB/CovidRetrieval
      config: default
      split: dev
      revision: 1271c7809071a13532e05f25fb53511ffce77117
    metrics:
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    - type: map_at_100
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  - task:
      type: Classification
    dataset:
      name: MTEB IFlyTek
      type: C-MTEB/IFlyTek-classification
      config: default
      split: validation
      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
    metrics:
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      value: 49.018853405155824
    - type: f1
      value: 36.34797570897239
    - type: f1_weighted
      value: 46.595946626038284
    - type: main_score
      value: 49.018853405155824
  - task:
      type: Classification
    dataset:
      name: MTEB JDReview
      type: C-MTEB/JDReview-classification
      config: default
      split: test
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
    metrics:
    - type: accuracy
      value: 80.76923076923077
    - type: ap
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    - type: ap_weighted
      value: 43.91219315273788
    - type: f1
      value: 74.3959076760867
    - type: f1_weighted
      value: 82.41054854790659
    - type: main_score
      value: 80.76923076923077
  - task:
      type: STS
    dataset:
      name: MTEB LCQMC
      type: C-MTEB/LCQMC
      config: default
      split: test
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
    metrics:
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    - type: cosine_spearman
      value: 69.6209380589209
    - type: euclidean_pearson
      value: 68.13684291689385
    - type: euclidean_spearman
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    - type: main_score
      value: 69.6209380589209
    - type: manhattan_pearson
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    - type: manhattan_spearman
      value: 69.46732039256112
    - type: pearson
      value: 66.42169614903062
    - type: spearman
      value: 69.6209380589209
  - task:
      type: Reranking
    dataset:
      name: MTEB MMarcoReranking
      type: C-MTEB/Mmarco-reranking
      config: default
      split: dev
      revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
    metrics:
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      value: 28.40392786552284
    - type: map
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    - type: mrr
      value: 26.729761904761908
    - type: nAUC_map_diff1
      value: 11.013649297702722
    - type: nAUC_map_max
      value: 10.17419646298121
    - type: nAUC_map_std
      value: -0.8563449479185579
    - type: nAUC_mrr_diff1
      value: 10.279159084348438
    - type: nAUC_mrr_max
      value: 9.945986054772508
    - type: nAUC_mrr_std
      value: -0.7829405326492496
  - task:
      type: Retrieval
    dataset:
      name: MTEB MMarcoRetrieval
      type: C-MTEB/MMarcoRetrieval
      config: default
      split: dev
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
    metrics:
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    - type: map_at_10
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    - type: map_at_100
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    - type: map_at_1000
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    - type: map_at_20
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    - type: map_at_3
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    - type: map_at_5
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    - type: mrr_at_1
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    - type: mrr_at_100
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    - type: mrr_at_1000
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    - type: mrr_at_3
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    - type: ndcg_at_1000
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    - type: precision_at_1
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    - type: precision_at_10
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    - type: precision_at_100
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    - type: precision_at_20
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    - type: precision_at_3
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    - type: precision_at_5
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    - type: recall_at_1
      value: 65.179
    - type: recall_at_10
      value: 90.059
    - type: recall_at_100
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    - type: recall_at_1000
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    - type: recall_at_20
      value: 93.345
    - type: recall_at_3
      value: 80.158
    - type: recall_at_5
      value: 85.33
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (zh-CN)
      type: mteb/amazon_massive_intent
      config: zh-CN
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 66.3987895090787
    - type: f1
      value: 64.01687665476737
    - type: f1_weighted
      value: 65.22982874187167
    - type: main_score
      value: 66.3987895090787
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (zh-TW)
      type: mteb/amazon_massive_intent
      config: zh-TW
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 57.36045729657027
    - type: f1
      value: 56.21747468274314
    - type: f1_weighted
      value: 55.328390649701
    - type: main_score
      value: 57.36045729657027
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-CN)
      type: mteb/amazon_massive_scenario
      config: zh-CN
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 72.56893073301949
    - type: f1
      value: 72.51154136026366
    - type: f1_weighted
      value: 72.06311963012884
    - type: main_score
      value: 72.56893073301949
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-TW)
      type: mteb/amazon_massive_scenario
      config: zh-TW
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 65.85406859448555
    - type: f1
      value: 66.48372498308458
    - type: f1_weighted
      value: 64.55871847643539
    - type: main_score
      value: 65.85406859448555
  - task:
      type: Retrieval
    dataset:
      name: MTEB MedicalRetrieval
      type: C-MTEB/MedicalRetrieval
      config: default
      split: dev
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
    metrics:
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      value: 56.908
    - type: map_at_1
      value: 48.9
    - type: map_at_10
      value: 54.25
    - type: map_at_100
      value: 54.83
    - type: map_at_1000
      value: 54.882
    - type: map_at_20
      value: 54.56100000000001
    - type: map_at_3
      value: 52.849999999999994
    - type: map_at_5
      value: 53.68000000000001
    - type: mrr_at_1
      value: 48.8
    - type: mrr_at_10
      value: 54.199801587301565
    - type: mrr_at_100
      value: 54.77998734976407
    - type: mrr_at_1000
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    - type: mrr_at_20
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    - type: mrr_at_3
      value: 52.79999999999999
    - type: mrr_at_5
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    - type: nauc_map_at_1000_diff1
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    - type: precision_at_1
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    - type: precision_at_5
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    - type: recall_at_1
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    - type: recall_at_10
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    - type: recall_at_100
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    - type: recall_at_1000
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    - type: recall_at_20
      value: 69.8
    - type: recall_at_3
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    - type: recall_at_5
      value: 61.1
  - task:
      type: Classification
    dataset:
      name: MTEB MultilingualSentiment
      type: C-MTEB/MultilingualSentiment-classification
      config: default
      split: test
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
    metrics:
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      value: 73.31666666666668
    - type: f1
      value: 72.28836634231243
    - type: f1_weighted
      value: 72.28836634231241
    - type: main_score
      value: 73.31666666666668
  - task:
      type: PairClassification
    dataset:
      name: MTEB Ocnli
      type: C-MTEB/OCNLI
      config: default
      split: validation
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
    metrics:
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      value: 67.02761234434217
    - type: cosine_accuracy_threshold
      value: 65.14335870742798
    - type: cosine_ap
      value: 69.4885294263304
    - type: cosine_f1
      value: 71.27996381727725
    - type: cosine_f1_threshold
      value: 58.83575081825256
    - type: cosine_precision
      value: 62.34177215189873
    - type: cosine_recall
      value: 83.21013727560718
    - type: dot_accuracy
      value: 67.02761234434217
    - type: dot_accuracy_threshold
      value: 65.14337062835693
    - type: dot_ap
      value: 69.4885294263304
    - type: dot_f1
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    - type: dot_f1_threshold
      value: 58.83575677871704
    - type: dot_precision
      value: 62.34177215189873
    - type: dot_recall
      value: 83.21013727560718
    - type: euclidean_accuracy
      value: 67.02761234434217
    - type: euclidean_accuracy_threshold
      value: 83.49447250366211
    - type: euclidean_ap
      value: 69.4885294263304
    - type: euclidean_f1
      value: 71.27996381727725
    - type: euclidean_f1_threshold
      value: 90.7350480556488
    - type: euclidean_precision
      value: 62.34177215189873
    - type: euclidean_recall
      value: 83.21013727560718
    - type: main_score
      value: 69.4885294263304
    - type: manhattan_accuracy
      value: 66.91932864103953
    - type: manhattan_accuracy_threshold
      value: 1951.8356323242188
    - type: manhattan_ap
      value: 69.02432804239183
    - type: manhattan_f1
      value: 70.89991589571069
    - type: manhattan_f1_threshold
      value: 2201.4184951782227
    - type: manhattan_precision
      value: 58.909853249475894
    - type: manhattan_recall
      value: 89.01795142555439
    - type: max_ap
      value: 69.4885294263304
    - type: max_f1
      value: 71.27996381727725
    - type: max_precision
      value: 62.34177215189873
    - type: max_recall
      value: 89.01795142555439
    - type: similarity_accuracy
      value: 67.02761234434217
    - type: similarity_accuracy_threshold
      value: 65.14335870742798
    - type: similarity_ap
      value: 69.4885294263304
    - type: similarity_f1
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    - type: similarity_f1_threshold
      value: 58.83575081825256
    - type: similarity_precision
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    - type: similarity_recall
      value: 83.21013727560718
  - task:
      type: Classification
    dataset:
      name: MTEB OnlineShopping
      type: C-MTEB/OnlineShopping-classification
      config: default
      split: test
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
    metrics:
    - type: accuracy
      value: 90.09
    - type: ap
      value: 88.76450265603408
    - type: ap_weighted
      value: 88.76450265603408
    - type: f1
      value: 90.08779175324347
    - type: f1_weighted
      value: 90.08719838771795
    - type: main_score
      value: 90.09
  - task:
      type: STS
    dataset:
      name: MTEB PAWSX
      type: C-MTEB/PAWSX
      config: default
      split: test
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
    metrics:
    - type: cosine_pearson
      value: 14.271650876491588
    - type: cosine_spearman
      value: 15.088934657692937
    - type: euclidean_pearson
      value: 17.64991910323611
    - type: euclidean_spearman
      value: 15.11015719401991
    - type: main_score
      value: 15.088934657692937
    - type: manhattan_pearson
      value: 17.627416265380024
    - type: manhattan_spearman
      value: 15.186102501045864
    - type: pearson
      value: 14.271650876491588
    - type: spearman
      value: 15.088934657692937
  - task:
      type: STS
    dataset:
      name: MTEB QBQTC
      type: C-MTEB/QBQTC
      config: default
      split: test
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
    metrics:
    - type: cosine_pearson
      value: 31.42374000164117
    - type: cosine_spearman
      value: 34.11139115201034
    - type: euclidean_pearson
      value: 31.86846452982553
    - type: euclidean_spearman
      value: 34.11160345676575
    - type: main_score
      value: 34.11139115201034
    - type: manhattan_pearson
      value: 31.78171047507477
    - type: manhattan_spearman
      value: 34.03769440675436
    - type: pearson
      value: 31.42374000164117
    - type: spearman
      value: 34.11139115201034
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
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      value: 70.18092147138205
    - type: cosine_spearman
      value: 69.90638729067848
    - type: euclidean_pearson
      value: 68.5214594150794
    - type: euclidean_spearman
      value: 69.8926146345444
    - type: main_score
      value: 69.90638729067848
    - type: manhattan_pearson
      value: 68.96098064777406
    - type: manhattan_spearman
      value: 70.49810937340672
    - type: pearson
      value: 70.18092147138205
    - type: spearman
      value: 69.90638729067848
  - task:
      type: STS
    dataset:
      name: MTEB STSB
      type: C-MTEB/STSB
      config: default
      split: test
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
    metrics:
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      value: 78.99516686642797
    - type: cosine_spearman
      value: 79.32633637626917
    - type: euclidean_pearson
      value: 78.21051836357536
    - type: euclidean_spearman
      value: 79.32612616365205
    - type: main_score
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    - type: manhattan_pearson
      value: 78.18343539953231
    - type: manhattan_spearman
      value: 79.33355463587682
    - type: pearson
      value: 78.99516686642797
    - type: spearman
      value: 79.32633637626917
  - task:
      type: Reranking
    dataset:
      name: MTEB T2Reranking
      type: C-MTEB/T2Reranking
      config: default
      split: dev
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
    metrics:
    - type: main_score
      value: 66.50583475592573
    - type: map
      value: 66.50583475592573
    - type: mrr
      value: 76.66814435094733
    - type: nAUC_map_diff1
      value: -7.531687895205624
    - type: nAUC_map_max
      value: 31.536810866173976
    - type: nAUC_map_std
      value: 0.584045198013492
    - type: nAUC_mrr_diff1
      value: -5.20389538556461
    - type: nAUC_mrr_max
      value: 26.230205943854155
    - type: nAUC_mrr_std
      value: -2.321422405480513
  - task:
      type: Retrieval
    dataset:
      name: MTEB T2Retrieval
      type: C-MTEB/T2Retrieval
      config: default
      split: dev
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
    metrics:
    - type: main_score
      value: 84.048
    - type: map_at_1
      value: 27.250000000000004
    - type: map_at_10
      value: 76.43799999999999
    - type: map_at_100
      value: 80.066
    - type: map_at_1000
      value: 80.136
    - type: map_at_20
      value: 79.194
    - type: map_at_3
      value: 53.787
    - type: map_at_5
      value: 66.06
    - type: mrr_at_1
      value: 89.4660704892162
    - type: mrr_at_10
      value: 92.02673022274553
    - type: mrr_at_100
      value: 92.11951616133179
    - type: mrr_at_1000
      value: 92.12325682782645
    - type: mrr_at_20
      value: 92.08937202287764
    - type: mrr_at_3
      value: 91.55853644280776
    - type: mrr_at_5
      value: 91.85947454556089
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      value: -9.627767798276931
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    - type: nauc_mrr_at_1000_diff1
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    - type: nauc_ndcg_at_10_diff1
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  - task:
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    dataset:
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      type: C-MTEB/TNews-classification
      config: default
      split: validation
      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
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  - task:
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    dataset:
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      type: C-MTEB/ThuNewsClusteringP2P
      config: default
      split: test
      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
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    - type: v_measure
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  - task:
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    dataset:
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      type: C-MTEB/ThuNewsClusteringS2S
      config: default
      split: test
      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
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    - type: v_measure
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  - task:
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    dataset:
      name: MTEB VideoRetrieval
      type: C-MTEB/VideoRetrieval
      config: default
      split: dev
      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
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  - task:
      type: Classification
    dataset:
      name: MTEB Waimai
      type: C-MTEB/waimai-classification
      config: default
      split: test
      revision: 339287def212450dcaa9df8c22bf93e9980c7023
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  - task:
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    dataset:
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      type: lyon-nlp/alloprof
      config: default
      split: test
      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
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  - task:
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      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
      config: default
      split: test
      revision: 65393d0d7a08a10b4e348135e824f385d420b0fd
    metrics:
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  - task:
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    dataset:
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      type: lyon-nlp/alloprof
      config: default
      split: test
      revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
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  - task:
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      type: mteb/amazon_reviews_multi
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      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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  - task:
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      type: maastrichtlawtech/bsard
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      revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
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  - task:
      type: Clustering
    dataset:
      name: MTEB HALClusteringS2S
      type: lyon-nlp/clustering-hal-s2s
      config: default
      split: test
      revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
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  - task:
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      type: reciTAL/mlsum
      config: fr
      split: test
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
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  - task:
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      type: mteb/mtop_domain
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      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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  - task:
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    dataset:
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      type: mteb/mtop_intent
      config: fr
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 50.241152521139995
    - type: f1
      value: 34.39524038805554
    - type: f1_weighted
      value: 53.93775073819592
    - type: main_score
      value: 50.241152521139995
  - task:
      type: Classification
    dataset:
      name: MTEB MasakhaNEWSClassification (fra)
      type: mteb/masakhanews
      config: fra
      split: test
      revision: 18193f187b92da67168c655c9973a165ed9593dd
    metrics:
    - type: accuracy
      value: 83.34123222748818
    - type: f1
      value: 79.48624508308065
    - type: f1_weighted
      value: 83.20210238500908
    - type: main_score
      value: 83.34123222748818
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (fra)
      type: masakhane/masakhanews
      config: fra
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 71.51218291988776
    - type: v_measure
      value: 71.51218291988776
    - type: v_measure_std
      value: 35.6439739308977
    - type: main_score
      value: 60.155743100795725
    - type: v_measure
      value: 60.155743100795725
    - type: v_measure_std
      value: 28.180226808833797
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fr)
      type: mteb/amazon_massive_intent
      config: fr
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 59.048419636852735
    - type: f1
      value: 55.77513997227217
    - type: f1_weighted
      value: 57.65743868976365
    - type: main_score
      value: 59.048419636852735
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (fr)
      type: mteb/amazon_massive_scenario
      config: fr
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 67.2932078009415
    - type: f1
      value: 66.85444841091169
    - type: f1_weighted
      value: 66.78952167770717
    - type: main_score
      value: 67.2932078009415
  - task:
      type: Retrieval
    dataset:
      name: MTEB MintakaRetrieval (fr)
      type: jinaai/mintakaqa
      config: fr
      split: test
      revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
    metrics:
    - type: main_score
      value: 27.400000000000002
    - type: map_at_1
      value: 15.479000000000001
    - type: map_at_10
      value: 23.213
    - type: map_at_100
      value: 24.285
    - type: map_at_1000
      value: 24.397
    - type: map_at_20
      value: 23.741
    - type: map_at_3
      value: 20.973
    - type: map_at_5
      value: 22.212
    - type: mrr_at_1
      value: 15.47911547911548
    - type: mrr_at_10
      value: 23.21331071331073
    - type: mrr_at_100
      value: 24.28515184787565
    - type: mrr_at_1000
      value: 24.396606382776362
    - type: mrr_at_20
      value: 23.74068872679202
    - type: mrr_at_3
      value: 20.973245973245938
    - type: mrr_at_5
      value: 22.211984711984677
    - type: nauc_map_at_1000_diff1
      value: 23.49190518969821
    - type: nauc_map_at_1000_max
      value: 21.816535185868748
    - type: nauc_map_at_1000_std
      value: 7.898426575861743
    - type: nauc_map_at_100_diff1
      value: 23.455942061154243
    - type: nauc_map_at_100_max
      value: 21.80945301878854
    - type: nauc_map_at_100_std
      value: 7.903289282168091
    - type: nauc_map_at_10_diff1
      value: 23.674951138068714
    - type: nauc_map_at_10_max
      value: 21.969792385911845
    - type: nauc_map_at_10_std
      value: 7.889585005426794
    - type: nauc_map_at_1_diff1
      value: 29.069568522388433
    - type: nauc_map_at_1_max
      value: 19.942608291469913
    - type: nauc_map_at_1_std
      value: 3.1283142332992635
    - type: nauc_map_at_20_diff1
      value: 23.45502400622297
    - type: nauc_map_at_20_max
      value: 21.830527331051552
    - type: nauc_map_at_20_std
      value: 7.994053361768913
    - type: nauc_map_at_3_diff1
      value: 24.982668301358444
    - type: nauc_map_at_3_max
      value: 21.883837899231867
    - type: nauc_map_at_3_std
      value: 6.615976792964795
    - type: nauc_map_at_5_diff1
      value: 24.09866390229764
    - type: nauc_map_at_5_max
      value: 21.614008493220986
    - type: nauc_map_at_5_std
      value: 7.272332396807288
    - type: nauc_mrr_at_1000_diff1
      value: 23.49190518969821
    - type: nauc_mrr_at_1000_max
      value: 21.816535185868748
    - type: nauc_mrr_at_1000_std
      value: 7.898426575861743
    - type: nauc_mrr_at_100_diff1
      value: 23.455942061154243
    - type: nauc_mrr_at_100_max
      value: 21.80945301878854
    - type: nauc_mrr_at_100_std
      value: 7.903289282168091
    - type: nauc_mrr_at_10_diff1
      value: 23.674951138068714
    - type: nauc_mrr_at_10_max
      value: 21.969792385911845
    - type: nauc_mrr_at_10_std
      value: 7.889585005426794
    - type: nauc_mrr_at_1_diff1
      value: 29.069568522388433
    - type: nauc_mrr_at_1_max
      value: 19.942608291469913
    - type: nauc_mrr_at_1_std
      value: 3.1283142332992635
    - type: nauc_mrr_at_20_diff1
      value: 23.45502400622297
    - type: nauc_mrr_at_20_max
      value: 21.830527331051552
    - type: nauc_mrr_at_20_std
      value: 7.994053361768913
    - type: nauc_mrr_at_3_diff1
      value: 24.982668301358444
    - type: nauc_mrr_at_3_max
      value: 21.883837899231867
    - type: nauc_mrr_at_3_std
      value: 6.615976792964795
    - type: nauc_mrr_at_5_diff1
      value: 24.09866390229764
    - type: nauc_mrr_at_5_max
      value: 21.614008493220986
    - type: nauc_mrr_at_5_std
      value: 7.272332396807288
    - type: nauc_ndcg_at_1000_diff1
      value: 21.92872678950541
    - type: nauc_ndcg_at_1000_max
      value: 22.388970258338958
    - type: nauc_ndcg_at_1000_std
      value: 9.807006541293186
    - type: nauc_ndcg_at_100_diff1
      value: 20.903304276761364
    - type: nauc_ndcg_at_100_max
      value: 22.209897726716065
    - type: nauc_ndcg_at_100_std
      value: 10.075543107880176
    - type: nauc_ndcg_at_10_diff1
      value: 21.508944950669097
    - type: nauc_ndcg_at_10_max
      value: 22.709862035037514
    - type: nauc_ndcg_at_10_std
      value: 10.00450608801698
    - type: nauc_ndcg_at_1_diff1
      value: 29.069568522388433
    - type: nauc_ndcg_at_1_max
      value: 19.942608291469913
    - type: nauc_ndcg_at_1_std
      value: 3.1283142332992635
    - type: nauc_ndcg_at_20_diff1
      value: 20.803145422787512
    - type: nauc_ndcg_at_20_max
      value: 22.310429618526772
    - type: nauc_ndcg_at_20_std
      value: 10.366058782551438
    - type: nauc_ndcg_at_3_diff1
      value: 23.913619145125207
    - type: nauc_ndcg_at_3_max
      value: 22.441574203993245
    - type: nauc_ndcg_at_3_std
      value: 7.691311158754716
    - type: nauc_ndcg_at_5_diff1
      value: 22.4840009470751
    - type: nauc_ndcg_at_5_max
      value: 22.024641703222514
    - type: nauc_ndcg_at_5_std
      value: 8.803747702599477
    - type: nauc_precision_at_1000_diff1
      value: 17.037870101460467
    - type: nauc_precision_at_1000_max
      value: 42.30306938098229
    - type: nauc_precision_at_1000_std
      value: 54.251307689225115
    - type: nauc_precision_at_100_diff1
      value: 12.076659360813839
    - type: nauc_precision_at_100_max
      value: 23.254576247061777
    - type: nauc_precision_at_100_std
      value: 17.80398606936446
    - type: nauc_precision_at_10_diff1
      value: 16.05902741145243
    - type: nauc_precision_at_10_max
      value: 24.536458909415416
    - type: nauc_precision_at_10_std
      value: 15.281423796153165
    - type: nauc_precision_at_1_diff1
      value: 29.069568522388433
    - type: nauc_precision_at_1_max
      value: 19.942608291469913
    - type: nauc_precision_at_1_std
      value: 3.1283142332992635
    - type: nauc_precision_at_20_diff1
      value: 13.618514792543918
    - type: nauc_precision_at_20_max
      value: 23.357417389310335
    - type: nauc_precision_at_20_std
      value: 16.6297119945886
    - type: nauc_precision_at_3_diff1
      value: 21.3058697791068
    - type: nauc_precision_at_3_max
      value: 23.815582518552716
    - type: nauc_precision_at_3_std
      value: 10.358496834243757
    - type: nauc_precision_at_5_diff1
      value: 18.54677328441144
    - type: nauc_precision_at_5_max
      value: 22.987289739937104
    - type: nauc_precision_at_5_std
      value: 12.591593599364307
    - type: nauc_recall_at_1000_diff1
      value: 17.03787010146031
    - type: nauc_recall_at_1000_max
      value: 42.303069380982336
    - type: nauc_recall_at_1000_std
      value: 54.25130768922508
    - type: nauc_recall_at_100_diff1
      value: 12.076659360813771
    - type: nauc_recall_at_100_max
      value: 23.254576247061777
    - type: nauc_recall_at_100_std
      value: 17.80398606936441
    - type: nauc_recall_at_10_diff1
      value: 16.05902741145243
    - type: nauc_recall_at_10_max
      value: 24.536458909415412
    - type: nauc_recall_at_10_std
      value: 15.281423796153174
    - type: nauc_recall_at_1_diff1
      value: 29.069568522388433
    - type: nauc_recall_at_1_max
      value: 19.942608291469913
    - type: nauc_recall_at_1_std
      value: 3.1283142332992635
    - type: nauc_recall_at_20_diff1
      value: 13.618514792543923
    - type: nauc_recall_at_20_max
      value: 23.3574173893104
    - type: nauc_recall_at_20_std
      value: 16.629711994588593
    - type: nauc_recall_at_3_diff1
      value: 21.305869779106818
    - type: nauc_recall_at_3_max
      value: 23.815582518552738
    - type: nauc_recall_at_3_std
      value: 10.358496834243747
    - type: nauc_recall_at_5_diff1
      value: 18.546773284411426
    - type: nauc_recall_at_5_max
      value: 22.987289739937083
    - type: nauc_recall_at_5_std
      value: 12.591593599364312
    - type: ndcg_at_1
      value: 15.479000000000001
    - type: ndcg_at_10
      value: 27.400000000000002
    - type: ndcg_at_100
      value: 33.382
    - type: ndcg_at_1000
      value: 36.691
    - type: ndcg_at_20
      value: 29.352
    - type: ndcg_at_3
      value: 22.759999999999998
    - type: ndcg_at_5
      value: 25.006
    - type: precision_at_1
      value: 15.479000000000001
    - type: precision_at_10
      value: 4.075
    - type: precision_at_100
      value: 0.7040000000000001
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_20
      value: 2.426
    - type: precision_at_3
      value: 9.309000000000001
    - type: precision_at_5
      value: 6.683
    - type: recall_at_1
      value: 15.479000000000001
    - type: recall_at_10
      value: 40.745
    - type: recall_at_100
      value: 70.434
    - type: recall_at_1000
      value: 97.21499999999999
    - type: recall_at_20
      value: 48.526
    - type: recall_at_3
      value: 27.927999999999997
    - type: recall_at_5
      value: 33.415
  - task:
      type: PairClassification
    dataset:
      name: MTEB OpusparcusPC (fr)
      type: GEM/opusparcus
      config: fr
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    metrics:
    - type: cosine_accuracy
      value: 82.42506811989101
    - type: cosine_accuracy_threshold
      value: 59.91581678390503
    - type: cosine_ap
      value: 92.86245135331164
    - type: cosine_f1
      value: 88.0
    - type: cosine_f1_threshold
      value: 59.91581678390503
    - type: cosine_precision
      value: 82.76465441819772
    - type: cosine_recall
      value: 93.94240317775571
    - type: dot_accuracy
      value: 82.42506811989101
    - type: dot_accuracy_threshold
      value: 59.91581678390503
    - type: dot_ap
      value: 92.86245135331164
    - type: dot_f1
      value: 88.0
    - type: dot_f1_threshold
      value: 59.91581678390503
    - type: dot_precision
      value: 82.76465441819772
    - type: dot_recall
      value: 93.94240317775571
    - type: euclidean_accuracy
      value: 82.42506811989101
    - type: euclidean_accuracy_threshold
      value: 89.53677415847778
    - type: euclidean_ap
      value: 92.86245135331164
    - type: euclidean_f1
      value: 88.0
    - type: euclidean_f1_threshold
      value: 89.53677415847778
    - type: euclidean_precision
      value: 82.76465441819772
    - type: euclidean_recall
      value: 93.94240317775571
    - type: main_score
      value: 92.86245135331164
    - type: manhattan_accuracy
      value: 82.28882833787466
    - type: manhattan_accuracy_threshold
      value: 2091.843032836914
    - type: manhattan_ap
      value: 92.84258977975239
    - type: manhattan_f1
      value: 87.88443616029824
    - type: manhattan_f1_threshold
      value: 2091.843032836914
    - type: manhattan_precision
      value: 82.79192273924495
    - type: manhattan_recall
      value: 93.64448857994041
    - type: max_ap
      value: 92.86245135331164
    - type: max_f1
      value: 88.0
    - type: max_precision
      value: 82.79192273924495
    - type: max_recall
      value: 93.94240317775571
    - type: similarity_accuracy
      value: 82.42506811989101
    - type: similarity_accuracy_threshold
      value: 59.91581678390503
    - type: similarity_ap
      value: 92.86245135331164
    - type: similarity_f1
      value: 88.0
    - type: similarity_f1_threshold
      value: 59.91581678390503
    - type: similarity_precision
      value: 82.76465441819772
    - type: similarity_recall
      value: 93.94240317775571
  - task:
      type: PairClassification
    dataset:
      name: MTEB PawsXPairClassification (fr)
      type: google-research-datasets/paws-x
      config: fr
      split: test
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
    metrics:
    - type: cosine_accuracy
      value: 61.050000000000004
    - type: cosine_accuracy_threshold
      value: 98.11633825302124
    - type: cosine_ap
      value: 60.385395031891264
    - type: cosine_f1
      value: 62.60428001450852
    - type: cosine_f1_threshold
      value: 89.5184874534607
    - type: cosine_precision
      value: 46.54800431499461
    - type: cosine_recall
      value: 95.5703211517165
    - type: dot_accuracy
      value: 61.050000000000004
    - type: dot_accuracy_threshold
      value: 98.11633825302124
    - type: dot_ap
      value: 60.37120015758097
    - type: dot_f1
      value: 62.60428001450852
    - type: dot_f1_threshold
      value: 89.5184874534607
    - type: dot_precision
      value: 46.54800431499461
    - type: dot_recall
      value: 95.5703211517165
    - type: euclidean_accuracy
      value: 61.050000000000004
    - type: euclidean_accuracy_threshold
      value: 19.409586489200592
    - type: euclidean_ap
      value: 60.385395031891264
    - type: euclidean_f1
      value: 62.60428001450852
    - type: euclidean_f1_threshold
      value: 45.78540325164795
    - type: euclidean_precision
      value: 46.54800431499461
    - type: euclidean_recall
      value: 95.5703211517165
    - type: main_score
      value: 60.61779879922903
    - type: manhattan_accuracy
      value: 61.0
    - type: manhattan_accuracy_threshold
      value: 455.7579040527344
    - type: manhattan_ap
      value: 60.61779879922903
    - type: manhattan_f1
      value: 62.56448047162859
    - type: manhattan_f1_threshold
      value: 1030.442714691162
    - type: manhattan_precision
      value: 46.880176697956934
    - type: manhattan_recall
      value: 94.01993355481729
    - type: max_ap
      value: 60.61779879922903
    - type: max_f1
      value: 62.60428001450852
    - type: max_precision
      value: 46.880176697956934
    - type: max_recall
      value: 95.5703211517165
    - type: similarity_accuracy
      value: 61.050000000000004
    - type: similarity_accuracy_threshold
      value: 98.11633825302124
    - type: similarity_ap
      value: 60.385395031891264
    - type: similarity_f1
      value: 62.60428001450852
    - type: similarity_f1_threshold
      value: 89.5184874534607
    - type: similarity_precision
      value: 46.54800431499461
    - type: similarity_recall
      value: 95.5703211517165
  - task:
      type: STS
    dataset:
      name: MTEB SICKFr
      type: Lajavaness/SICK-fr
      config: default
      split: test
      revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
    metrics:
    - type: cosine_pearson
      value: 81.36950266249254
    - type: cosine_spearman
      value: 77.4306890341242
    - type: euclidean_pearson
      value: 77.47472965962992
    - type: euclidean_spearman
      value: 77.431649040768
    - type: main_score
      value: 77.4306890341242
    - type: manhattan_pearson
      value: 77.44468465408777
    - type: manhattan_spearman
      value: 77.25503240591341
    - type: pearson
      value: 81.36950266249254
    - type: spearman
      value: 77.4306890341242
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 81.48671869348665
    - type: cosine_spearman
      value: 82.57396913836067
    - type: euclidean_pearson
      value: 81.71206012505978
    - type: euclidean_spearman
      value: 82.64978141643995
    - type: main_score
      value: 82.57396913836067
    - type: manhattan_pearson
      value: 82.22351352342636
    - type: manhattan_spearman
      value: 83.04856400618516
    - type: pearson
      value: 81.48671869348665
    - type: spearman
      value: 82.57396913836067
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-fr)
      type: mteb/sts22-crosslingual-sts
      config: de-fr
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 60.45418014677442
    - type: cosine_spearman
      value: 64.66584550775643
    - type: euclidean_pearson
      value: 60.042908719941124
    - type: euclidean_spearman
      value: 64.66584550775643
    - type: main_score
      value: 64.66584550775643
    - type: manhattan_pearson
      value: 58.56106956676841
    - type: manhattan_spearman
      value: 64.07469227945803
    - type: pearson
      value: 60.45418014677442
    - type: spearman
      value: 64.66584550775643
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 83.39169883126554
    - type: cosine_spearman
      value: 84.51542547285167
    - type: euclidean_pearson
      value: 83.79128537281704
    - type: euclidean_spearman
      value: 84.51542547285167
    - type: main_score
      value: 84.51542547285167
    - type: manhattan_pearson
      value: 82.282109060827
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    - type: pearson
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    - type: spearman
      value: 84.51542547285167
    - type: cosine_pearson
      value: 83.39168516605531
    - type: cosine_spearman
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    - type: euclidean_pearson
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    - type: euclidean_spearman
      value: 84.51542547285167
    - type: main_score
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      value: 84.51542547285167
    - type: pearson
      value: 83.39168516605531
    - type: spearman
      value: 84.51542547285167
  - task:
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    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (fr)
      type: mteb/stsb_multi_mt
      config: fr
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
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      value: 81.23994381619546
    - type: cosine_spearman
      value: 81.55923116292537
    - type: euclidean_pearson
      value: 79.95507984767936
    - type: euclidean_spearman
      value: 81.55780186152964
    - type: main_score
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    - type: manhattan_pearson
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    - type: manhattan_spearman
      value: 81.47864706229939
    - type: pearson
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    - type: spearman
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  - task:
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    dataset:
      name: MTEB SummEvalFr
      type: lyon-nlp/summarization-summeval-fr-p2p
      config: default
      split: test
      revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
    metrics:
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    - type: dot_pearson
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    - type: dot_spearman
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    - type: main_score
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    - type: pearson
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    - type: spearman
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  - task:
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    dataset:
      name: MTEB SyntecReranking
      type: lyon-nlp/mteb-fr-reranking-syntec-s2p
      config: default
      split: test
      revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad
    metrics:
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    - type: mrr
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    - type: nAUC_map_diff1
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  - task:
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    dataset:
      name: MTEB SyntecRetrieval
      type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
      config: default
      split: test
      revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9
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    - type: ndcg_at_1
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    - type: recall_at_1
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  - task:
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    dataset:
      name: MTEB XPQARetrieval (fr)
      type: jinaai/xpqa
      config: fra-fra
      split: test
      revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
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  - task:
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  - task:
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  - task:
      type: Classification
    dataset:
      name: MTEB AllegroReviews
      type: PL-MTEB/allegro-reviews
      config: default
      split: test
      revision: b89853e6de927b0e3bfa8ecc0e56fe4e02ceafc6
    metrics:
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    - type: f1_weighted
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    - type: main_score
      value: 49.22465208747514
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna-PL
      type: clarin-knext/arguana-pl
      config: default
      split: test
      revision: 63fc86750af76253e8c760fc9e534bbf24d260a2
    metrics:
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    - type: map_at_100
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    - type: precision_at_1
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    - type: precision_at_1000
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    - type: precision_at_3
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    - type: precision_at_5
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    - type: recall_at_1
      value: 24.751
    - type: recall_at_10
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    - type: recall_at_100
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    - type: recall_at_1000
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    - type: recall_at_20
      value: 89.972
    - type: recall_at_3
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    - type: recall_at_5
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  - task:
      type: Classification
    dataset:
      name: MTEB CBD
      type: PL-MTEB/cbd
      config: default
      split: test
      revision: 36ddb419bcffe6a5374c3891957912892916f28d
    metrics:
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    - type: ap
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    - type: ap_weighted
      value: 18.744713128220596
    - type: f1
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    - type: f1_weighted
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    - type: main_score
      value: 62.85999999999999
  - task:
      type: PairClassification
    dataset:
      name: MTEB CDSC-E
      type: PL-MTEB/cdsce-pairclassification
      config: default
      split: test
      revision: 0a3d4aa409b22f80eb22cbf59b492637637b536d
    metrics:
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      value: 87.3
    - type: cosine_accuracy_threshold
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    - type: cosine_ap
      value: 69.77225668650979
    - type: cosine_f1
      value: 63.04909560723513
    - type: cosine_f1_threshold
      value: 86.9259238243103
    - type: cosine_precision
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    - type: cosine_recall
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    - type: dot_accuracy
      value: 87.3
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    - type: dot_ap
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    - type: dot_f1
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    - type: dot_f1_threshold
      value: 86.9259238243103
    - type: dot_precision
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    - type: dot_recall
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    - type: euclidean_accuracy
      value: 87.3
    - type: euclidean_accuracy_threshold
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    - type: euclidean_ap
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    - type: euclidean_f1_threshold
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    - type: euclidean_precision
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    - type: euclidean_recall
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    - type: main_score
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    - type: manhattan_accuracy
      value: 87.5
    - type: manhattan_accuracy_threshold
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    - type: manhattan_ap
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      value: 63.54166666666667
    - type: manhattan_f1_threshold
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    - type: manhattan_precision
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    - type: manhattan_recall
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    - type: max_ap
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    - type: max_f1
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    - type: max_precision
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    - type: max_recall
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    - type: similarity_accuracy
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    - type: similarity_accuracy_threshold
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    - type: similarity_ap
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    - type: similarity_f1
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    - type: similarity_precision
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  - task:
      type: STS
    dataset:
      name: MTEB CDSC-R
      type: PL-MTEB/cdscr-sts
      config: default
      split: test
      revision: 1cd6abbb00df7d14be3dbd76a7dcc64b3a79a7cd
    metrics:
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    - type: euclidean_pearson
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    - type: euclidean_spearman
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    - type: manhattan_spearman
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    - type: pearson
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  - task:
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    dataset:
      name: MTEB DBPedia-PL
      type: clarin-knext/dbpedia-pl
      config: default
      split: test
      revision: 76afe41d9af165cc40999fcaa92312b8b012064a
    metrics:
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  - task:
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  - task:
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  - task:
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    dataset:
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      type: clarin-knext/nq-pl
      config: default
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      revision: f171245712cf85dd4700b06bef18001578d0ca8d
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  - task:
      type: Classification
    dataset:
      name: MTEB PAC
      type: laugustyniak/abusive-clauses-pl
      config: default
      split: test
      revision: fc69d1c153a8ccdcf1eef52f4e2a27f88782f543
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  - task:
      type: PairClassification
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      name: MTEB PSC
      type: PL-MTEB/psc-pairclassification
      config: default
      split: test
      revision: d05a294af9e1d3ff2bfb6b714e08a24a6cabc669
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  - task:
      type: Classification
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      type: PL-MTEB/polemo2_in
      config: default
      split: test
      revision: d90724373c70959f17d2331ad51fb60c71176b03
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  - task:
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      type: PL-MTEB/polemo2_out
      config: default
      split: test
      revision: 6a21ab8716e255ab1867265f8b396105e8aa63d4
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  - task:
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      type: PL-MTEB/ppc-pairclassification
      config: default
      split: test
      revision: 2c7d2df57801a591f6b1e3aaf042e7a04ec7d9f2
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  - task:
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      type: clarin-knext/quora-pl
      config: default
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      revision: 0be27e93455051e531182b85e85e425aba12e9d4
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  - task:
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      type: clarin-knext/scidocs-pl
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    - type: nauc_precision_at_20_diff1
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    - type: nauc_precision_at_20_max
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      value: 28.057493966763282
    - type: nauc_precision_at_5_std
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    - type: nauc_recall_at_1000_max
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    - type: nauc_recall_at_1000_std
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    - type: nauc_recall_at_100_std
      value: 37.184544204955074
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      value: 10.47166367371188
    - type: nauc_recall_at_10_max
      value: 29.14586678828798
    - type: nauc_recall_at_10_std
      value: 22.111878920453464
    - type: nauc_recall_at_1_diff1
      value: 21.132398215573865
    - type: nauc_recall_at_1_max
      value: 29.19592327750959
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      value: 7.4486268209490465
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      value: 28.572542534889312
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      value: 17.816298041992443
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      value: 11.600069164989952
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      value: 27.974947140469958
    - type: nauc_recall_at_5_std
      value: 19.139625890938866
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      value: 13.700000000000001
    - type: ndcg_at_10
      value: 13.038
    - type: ndcg_at_100
      value: 19.628
    - type: ndcg_at_1000
      value: 24.892
    - type: ndcg_at_20
      value: 15.296999999999999
    - type: ndcg_at_3
      value: 11.828
    - type: ndcg_at_5
      value: 10.532
    - type: precision_at_1
      value: 13.700000000000001
    - type: precision_at_10
      value: 6.99
    - type: precision_at_100
      value: 1.659
    - type: precision_at_1000
      value: 0.294
    - type: precision_at_20
      value: 4.8
    - type: precision_at_3
      value: 11.233
    - type: precision_at_5
      value: 9.44
    - type: recall_at_1
      value: 2.785
    - type: recall_at_10
      value: 14.198
    - type: recall_at_100
      value: 33.768
    - type: recall_at_1000
      value: 59.821999999999996
    - type: recall_at_20
      value: 19.497999999999998
    - type: recall_at_3
      value: 6.877999999999999
    - type: recall_at_5
      value: 9.613
  - task:
      type: PairClassification
    dataset:
      name: MTEB SICK-E-PL
      type: PL-MTEB/sicke-pl-pairclassification
      config: default
      split: test
      revision: 71bba34b0ece6c56dfcf46d9758a27f7a90f17e9
    metrics:
    - type: cosine_accuracy
      value: 77.45617611088463
    - type: cosine_accuracy_threshold
      value: 88.67492079734802
    - type: cosine_ap
      value: 62.798198995025665
    - type: cosine_f1
      value: 60.74950690335306
    - type: cosine_f1_threshold
      value: 80.56387305259705
    - type: cosine_precision
      value: 50.256410256410255
    - type: cosine_recall
      value: 76.78062678062678
    - type: dot_accuracy
      value: 77.45617611088463
    - type: dot_accuracy_threshold
      value: 88.6749267578125
    - type: dot_ap
      value: 62.798159152951385
    - type: dot_f1
      value: 60.74950690335306
    - type: dot_f1_threshold
      value: 80.56387305259705
    - type: dot_precision
      value: 50.256410256410255
    - type: dot_recall
      value: 76.78062678062678
    - type: euclidean_accuracy
      value: 77.45617611088463
    - type: euclidean_accuracy_threshold
      value: 47.592175006866455
    - type: euclidean_ap
      value: 62.79814750094985
    - type: euclidean_f1
      value: 60.74950690335306
    - type: euclidean_f1_threshold
      value: 62.347614765167236
    - type: euclidean_precision
      value: 50.256410256410255
    - type: euclidean_recall
      value: 76.78062678062678
    - type: main_score
      value: 62.798198995025665
    - type: manhattan_accuracy
      value: 77.27272727272727
    - type: manhattan_accuracy_threshold
      value: 975.9557723999023
    - type: manhattan_ap
      value: 62.33701490592974
    - type: manhattan_f1
      value: 60.3921568627451
    - type: manhattan_f1_threshold
      value: 1475.3839492797852
    - type: manhattan_precision
      value: 49.769159741458914
    - type: manhattan_recall
      value: 76.78062678062678
    - type: max_ap
      value: 62.798198995025665
    - type: max_f1
      value: 60.74950690335306
    - type: max_precision
      value: 50.256410256410255
    - type: max_recall
      value: 76.78062678062678
    - type: similarity_accuracy
      value: 77.45617611088463
    - type: similarity_accuracy_threshold
      value: 88.67492079734802
    - type: similarity_ap
      value: 62.798198995025665
    - type: similarity_f1
      value: 60.74950690335306
    - type: similarity_f1_threshold
      value: 80.56387305259705
    - type: similarity_precision
      value: 50.256410256410255
    - type: similarity_recall
      value: 76.78062678062678
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R-PL
      type: PL-MTEB/sickr-pl-sts
      config: default
      split: test
      revision: fd5c2441b7eeff8676768036142af4cfa42c1339
    metrics:
    - type: cosine_pearson
      value: 72.36287255590445
    - type: cosine_spearman
      value: 66.30825825122318
    - type: euclidean_pearson
      value: 68.92313932419128
    - type: euclidean_spearman
      value: 66.30826006369618
    - type: main_score
      value: 66.30825825122318
    - type: manhattan_pearson
      value: 68.66991543703946
    - type: manhattan_spearman
      value: 66.0242047018923
    - type: pearson
      value: 72.36287255590445
    - type: spearman
      value: 66.30825825122318
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 41.56662243222903
    - type: cosine_spearman
      value: 44.94984671604992
    - type: euclidean_pearson
      value: 27.88886658631932
    - type: euclidean_spearman
      value: 44.94984671604992
    - type: main_score
      value: 44.94984671604992
    - type: manhattan_pearson
      value: 27.467462847157798
    - type: manhattan_spearman
      value: 44.990280944902125
    - type: pearson
      value: 41.56662243222903
    - type: spearman
      value: 44.94984671604992
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 38.70216637556677
    - type: cosine_spearman
      value: 55.768121437825556
    - type: euclidean_pearson
      value: 41.389482428930485
    - type: euclidean_spearman
      value: 55.768121437825556
    - type: main_score
      value: 55.768121437825556
    - type: manhattan_pearson
      value: 42.7616496232802
    - type: manhattan_spearman
      value: 54.44397498734157
    - type: pearson
      value: 38.70216637556677
    - type: spearman
      value: 55.768121437825556
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact-PL
      type: clarin-knext/scifact-pl
      config: default
      split: test
      revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e
    metrics:
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      value: 57.827
    - type: map_at_1
      value: 45.083
    - type: map_at_10
      value: 53.83
    - type: map_at_100
      value: 54.577
    - type: map_at_1000
      value: 54.623
    - type: map_at_20
      value: 54.211
    - type: map_at_3
      value: 51.304
    - type: map_at_5
      value: 52.851000000000006
    - type: mrr_at_1
      value: 47.333333333333336
    - type: mrr_at_10
      value: 55.07949735449736
    - type: mrr_at_100
      value: 55.710506477168956
    - type: mrr_at_1000
      value: 55.748401782889445
    - type: mrr_at_20
      value: 55.409548920578345
    - type: mrr_at_3
      value: 53.055555555555564
    - type: mrr_at_5
      value: 54.422222222222224
    - type: nauc_map_at_1000_diff1
      value: 56.75114793396484
    - type: nauc_map_at_1000_max
      value: 45.557101118136366
    - type: nauc_map_at_1000_std
      value: 21.122840914857495
    - type: nauc_map_at_100_diff1
      value: 56.738747688350024
    - type: nauc_map_at_100_max
      value: 45.55491958094813
    - type: nauc_map_at_100_std
      value: 21.12266632389643
    - type: nauc_map_at_10_diff1
      value: 56.926041668030855
    - type: nauc_map_at_10_max
      value: 45.2382783831653
    - type: nauc_map_at_10_std
      value: 20.922255034211766
    - type: nauc_map_at_1_diff1
      value: 60.98838903764472
    - type: nauc_map_at_1_max
      value: 43.22668392792625
    - type: nauc_map_at_1_std
      value: 17.29004046426385
    - type: nauc_map_at_20_diff1
      value: 56.848541422173795
    - type: nauc_map_at_20_max
      value: 45.59725008207042
    - type: nauc_map_at_20_std
      value: 21.177613569735655
    - type: nauc_map_at_3_diff1
      value: 58.23995403356206
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      value: 44.76675994666382
    - type: nauc_map_at_3_std
      value: 18.839553176727783
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      value: 56.99049510687553
    - type: nauc_map_at_5_max
      value: 44.71681163401595
    - type: nauc_map_at_5_std
      value: 19.453824672770455
    - type: nauc_mrr_at_1000_diff1
      value: 57.4953870158563
    - type: nauc_mrr_at_1000_max
      value: 46.79551970939633
    - type: nauc_mrr_at_1000_std
      value: 23.71693511404122
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      value: 57.482272276265235
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      value: 46.79105970491737
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      value: 23.705546007429124
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      value: 57.630280158288926
    - type: nauc_mrr_at_10_max
      value: 46.646619843739465
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      value: 23.642389853421577
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      value: 61.903420841877356
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      value: 46.95318894276891
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      value: 23.19343113872584
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      value: 46.825490821786545
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      value: 58.634726160884576
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      value: 46.68634348254961
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      value: 22.9939558189414
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      value: 57.43527378441584
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      value: 46.82233838319152
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      value: 23.407766325712398
    - type: nauc_ndcg_at_1000_diff1
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      value: 46.703610191621145
    - type: nauc_ndcg_at_1000_std
      value: 23.57730795756405
    - type: nauc_ndcg_at_100_diff1
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      value: 46.37493158024567
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      value: 45.58511788479343
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      value: 46.95318894276891
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      value: 54.96359325487391
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      value: 46.525071413272975
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      value: 57.33303538179732
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      value: 45.60081314229553
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      value: 20.311802683707644
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      value: 55.09370926297347
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      value: 45.11375173156922
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      value: 20.676971796560167
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      value: 41.57287780821485
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      value: 46.95318894276891
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      value: 37.54978789546971
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      value: 46.25836394647075
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      value: 25.448947126738393
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      value: 34.21739846774853
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      value: 43.36271521542134
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      value: 28.863168300518954
    - type: nauc_recall_at_1000_diff1
      value: 50.866272434900374
    - type: nauc_recall_at_1000_max
      value: 77.90745928000882
    - type: nauc_recall_at_1000_std
      value: 82.21288515406151
    - type: nauc_recall_at_100_diff1
      value: 35.307317119527056
    - type: nauc_recall_at_100_max
      value: 46.922433638935956
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      value: 31.814942138236262
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    - type: nauc_recall_at_10_max
      value: 43.310991487523246
    - type: nauc_recall_at_10_std
      value: 25.903501909176917
    - type: nauc_recall_at_1_diff1
      value: 60.98838903764472
    - type: nauc_recall_at_1_max
      value: 43.22668392792625
    - type: nauc_recall_at_1_std
      value: 17.29004046426385
    - type: nauc_recall_at_20_diff1
      value: 45.83142943406739
    - type: nauc_recall_at_20_max
      value: 46.73030342771932
    - type: nauc_recall_at_20_std
      value: 28.07957120284036
    - type: nauc_recall_at_3_diff1
      value: 54.187633219194495
    - type: nauc_recall_at_3_max
      value: 43.672283626861066
    - type: nauc_recall_at_3_std
      value: 18.136469354114993
    - type: nauc_recall_at_5_diff1
      value: 47.4292849527445
    - type: nauc_recall_at_5_max
      value: 42.22276792180875
    - type: nauc_recall_at_5_std
      value: 19.22371392434811
    - type: ndcg_at_1
      value: 47.333
    - type: ndcg_at_10
      value: 57.827
    - type: ndcg_at_100
      value: 61.551
    - type: ndcg_at_1000
      value: 62.865
    - type: ndcg_at_20
      value: 59.03699999999999
    - type: ndcg_at_3
      value: 53.554
    - type: ndcg_at_5
      value: 55.949000000000005
    - type: precision_at_1
      value: 47.333
    - type: precision_at_10
      value: 7.767
    - type: precision_at_100
      value: 0.987
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_20
      value: 4.167
    - type: precision_at_3
      value: 21.111
    - type: precision_at_5
      value: 14.133000000000001
    - type: recall_at_1
      value: 45.083
    - type: recall_at_10
      value: 68.667
    - type: recall_at_100
      value: 86.433
    - type: recall_at_1000
      value: 97.0
    - type: recall_at_20
      value: 73.078
    - type: recall_at_3
      value: 57.477999999999994
    - type: recall_at_5
      value: 63.322
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID-PL
      type: clarin-knext/trec-covid-pl
      config: default
      split: test
      revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd
    metrics:
    - type: main_score
      value: 56.919
    - type: map_at_1
      value: 0.17600000000000002
    - type: map_at_10
      value: 1.352
    - type: map_at_100
      value: 7.253
    - type: map_at_1000
      value: 18.698
    - type: map_at_20
      value: 2.313
    - type: map_at_3
      value: 0.496
    - type: map_at_5
      value: 0.775
    - type: mrr_at_1
      value: 68.0
    - type: mrr_at_10
      value: 80.26904761904761
    - type: mrr_at_100
      value: 80.26904761904761
    - type: mrr_at_1000
      value: 80.26904761904761
    - type: mrr_at_20
      value: 80.26904761904761
    - type: mrr_at_3
      value: 78.33333333333333
    - type: mrr_at_5
      value: 79.73333333333332
    - type: nauc_map_at_1000_diff1
      value: 6.574463369141221
    - type: nauc_map_at_1000_max
      value: 53.38255229751684
    - type: nauc_map_at_1000_std
      value: 80.05902957099651
    - type: nauc_map_at_100_diff1
      value: 11.446821053406707
    - type: nauc_map_at_100_max
      value: 44.68607496071329
    - type: nauc_map_at_100_std
      value: 72.78356846807002
    - type: nauc_map_at_10_diff1
      value: 19.670014556837902
    - type: nauc_map_at_10_max
      value: 34.81097303843686
    - type: nauc_map_at_10_std
      value: 33.674183618423335
    - type: nauc_map_at_1_diff1
      value: 21.506439684761883
    - type: nauc_map_at_1_max
      value: 28.484715735575577
    - type: nauc_map_at_1_std
      value: 9.63153171871658
    - type: nauc_map_at_20_diff1
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    - type: ndcg_at_1
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    - type: ndcg_at_1000
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    - type: precision_at_1
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    - type: precision_at_100
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    - type: precision_at_1000
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    - type: precision_at_3
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    - type: precision_at_5
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    - type: recall_at_1
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    - type: recall_at_10
      value: 1.637
    - type: recall_at_100
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    - type: recall_at_1000
      value: 40.766999999999996
    - type: recall_at_20
      value: 2.983
    - type: recall_at_3
      value: 0.5519999999999999
    - type: recall_at_5
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  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB CEDRClassification
      type: ai-forever/cedr-classification
      config: default
      split: test
      revision: c0ba03d058e3e1b2f3fd20518875a4563dd12db4
    metrics:
    - type: accuracy
      value: 42.15727948990436
    - type: f1
      value: 39.09194730362947
    - type: lrap
      value: 71.07199787460253
    - type: main_score
      value: 42.15727948990436
  - task:
      type: Classification
    dataset:
      name: MTEB GeoreviewClassification
      type: ai-forever/georeview-classification
      config: default
      split: test
      revision: 3765c0d1de6b7d264bc459433c45e5a75513839c
    metrics:
    - type: accuracy
      value: 47.685546875
    - type: f1
      value: 42.201867616479085
    - type: f1_weighted
      value: 42.20127250813618
    - type: main_score
      value: 47.685546875
  - task:
      type: Clustering
    dataset:
      name: MTEB GeoreviewClusteringP2P
      type: ai-forever/georeview-clustering-p2p
      config: default
      split: test
      revision: 97a313c8fc85b47f13f33e7e9a95c1ad888c7fec
    metrics:
    - type: main_score
      value: 63.39849666467603
    - type: v_measure
      value: 63.39849666467603
    - type: v_measure_std
      value: 0.4433669974776044
  - task:
      type: Classification
    dataset:
      name: MTEB HeadlineClassification
      type: ai-forever/headline-classification
      config: default
      split: test
      revision: 2fe05ee6b5832cda29f2ef7aaad7b7fe6a3609eb
    metrics:
    - type: accuracy
      value: 83.45703125
    - type: f1
      value: 83.44147121320216
    - type: f1_weighted
      value: 83.43953816781061
    - type: main_score
      value: 83.45703125
  - task:
      type: Classification
    dataset:
      name: MTEB InappropriatenessClassification
      type: ai-forever/inappropriateness-classification
      config: default
      split: test
      revision: 601651fdc45ef243751676e62dd7a19f491c0285
    metrics:
    - type: accuracy
      value: 61.318359375
    - type: ap
      value: 57.103049962056815
    - type: ap_weighted
      value: 57.103049962056815
    - type: f1
      value: 60.69364450664112
    - type: f1_weighted
      value: 60.69364450664112
    - type: main_score
      value: 61.318359375
  - task:
      type: Classification
    dataset:
      name: MTEB KinopoiskClassification
      type: ai-forever/kinopoisk-sentiment-classification
      config: default
      split: test
      revision: 5911f26666ac11af46cb9c6849d0dc80a378af24
    metrics:
    - type: accuracy
      value: 59.040000000000006
    - type: f1
      value: 55.63433742720159
    - type: f1_weighted
      value: 55.63433742720159
    - type: main_score
      value: 59.040000000000006
  - task:
      type: Reranking
    dataset:
      name: MTEB MIRACLReranking (ru)
      type: miracl/mmteb-miracl-reranking
      config: ru
      split: dev
      revision: 6d1962c527217f8927fca80f890f14f36b2802af
    metrics:
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      value: 29.729
    - type: MAP@10(MIRACL)
      value: 48.713
    - type: MAP@100(MIRACL)
      value: 50.792
    - type: MAP@1000(MIRACL)
      value: 50.792
    - type: MAP@20(MIRACL)
      value: 50.197
    - type: MAP@3(MIRACL)
      value: 41.8
    - type: MAP@5(MIRACL)
      value: 45.706
    - type: NDCG@1(MIRACL)
      value: 49.158
    - type: NDCG@10(MIRACL)
      value: 56.550999999999995
    - type: NDCG@100(MIRACL)
      value: 60.829
    - type: NDCG@1000(MIRACL)
      value: 60.829
    - type: NDCG@20(MIRACL)
      value: 59.229
    - type: NDCG@3(MIRACL)
      value: 50.397000000000006
    - type: NDCG@5(MIRACL)
      value: 53.105000000000004
    - type: P@1(MIRACL)
      value: 49.158
    - type: P@10(MIRACL)
      value: 14.908
    - type: P@100(MIRACL)
      value: 1.9529999999999998
    - type: P@1000(MIRACL)
      value: 0.19499999999999998
    - type: P@20(MIRACL)
      value: 8.753
    - type: P@3(MIRACL)
      value: 31.061
    - type: P@5(MIRACL)
      value: 23.785
    - type: Recall@1(MIRACL)
      value: 29.729
    - type: Recall@10(MIRACL)
      value: 67.223
    - type: Recall@100(MIRACL)
      value: 79.952
    - type: Recall@1000(MIRACL)
      value: 79.952
    - type: Recall@20(MIRACL)
      value: 74.417
    - type: Recall@3(MIRACL)
      value: 49.073
    - type: Recall@5(MIRACL)
      value: 58.094
    - type: main_score
      value: 56.550999999999995
    - type: nAUC_MAP@1000_diff1(MIRACL)
      value: 19.222716664871324
    - type: nAUC_MAP@1000_max(MIRACL)
      value: 28.91315309273525
    - type: nAUC_MAP@1000_std(MIRACL)
      value: 15.773770301363973
    - type: nAUC_MAP@100_diff1(MIRACL)
      value: 19.222716664871324
    - type: nAUC_MAP@100_max(MIRACL)
      value: 28.91315309273525
    - type: nAUC_MAP@100_std(MIRACL)
      value: 15.773770301363973
    - type: nAUC_MAP@10_diff1(MIRACL)
      value: 21.16716217839532
    - type: nAUC_MAP@10_max(MIRACL)
      value: 26.58073750952478
    - type: nAUC_MAP@10_std(MIRACL)
      value: 14.98546699381452
    - type: nAUC_MAP@1_diff1(MIRACL)
      value: 37.50928508734578
    - type: nAUC_MAP@1_max(MIRACL)
      value: 13.158704351998995
    - type: nAUC_MAP@1_std(MIRACL)
      value: 4.422878276220556
    - type: nAUC_MAP@20_diff1(MIRACL)
      value: 19.951045759045467
    - type: nAUC_MAP@20_max(MIRACL)
      value: 28.25165991244302
    - type: nAUC_MAP@20_std(MIRACL)
      value: 15.850363419877105
    - type: nAUC_MAP@3_diff1(MIRACL)
      value: 27.774164479669988
    - type: nAUC_MAP@3_max(MIRACL)
      value: 20.738889611307496
    - type: nAUC_MAP@3_std(MIRACL)
      value: 9.22491952318088
    - type: nAUC_MAP@5_diff1(MIRACL)
      value: 23.86089217267443
    - type: nAUC_MAP@5_max(MIRACL)
      value: 23.19878810494586
    - type: nAUC_MAP@5_std(MIRACL)
      value: 11.851875808858123
    - type: nAUC_NDCG@1000_diff1(MIRACL)
      value: 9.459016218726891
    - type: nAUC_NDCG@1000_max(MIRACL)
      value: 38.018030050210896
    - type: nAUC_NDCG@1000_std(MIRACL)
      value: 20.555997574199246
    - type: nAUC_NDCG@100_diff1(MIRACL)
      value: 9.459016218726891
    - type: nAUC_NDCG@100_max(MIRACL)
      value: 38.018030050210896
    - type: nAUC_NDCG@100_std(MIRACL)
      value: 20.555997574199246
    - type: nAUC_NDCG@10_diff1(MIRACL)
      value: 14.2494195957649
    - type: nAUC_NDCG@10_max(MIRACL)
      value: 32.87676976986289
    - type: nAUC_NDCG@10_std(MIRACL)
      value: 19.469852065776976
    - type: nAUC_NDCG@1_diff1(MIRACL)
      value: 23.312659021070818
    - type: nAUC_NDCG@1_max(MIRACL)
      value: 31.554119919664593
    - type: nAUC_NDCG@1_std(MIRACL)
      value: 17.533789813864466
    - type: nAUC_NDCG@20_diff1(MIRACL)
      value: 11.694064829915717
    - type: nAUC_NDCG@20_max(MIRACL)
      value: 36.12122229242797
    - type: nAUC_NDCG@20_std(MIRACL)
      value: 20.886325245384313
    - type: nAUC_NDCG@3_diff1(MIRACL)
      value: 19.70964037059834
    - type: nAUC_NDCG@3_max(MIRACL)
      value: 28.271224651385758
    - type: nAUC_NDCG@3_std(MIRACL)
      value: 14.182889320426757
    - type: nAUC_NDCG@5_diff1(MIRACL)
      value: 17.143482434537635
    - type: nAUC_NDCG@5_max(MIRACL)
      value: 28.911278684121744
    - type: nAUC_NDCG@5_std(MIRACL)
      value: 15.83019582479379
    - type: nAUC_P@1000_diff1(MIRACL)
      value: -28.806220159210838
    - type: nAUC_P@1000_max(MIRACL)
      value: 30.19137414854295
    - type: nAUC_P@1000_std(MIRACL)
      value: 15.577217138606922
    - type: nAUC_P@100_diff1(MIRACL)
      value: -28.8062201592108
    - type: nAUC_P@100_max(MIRACL)
      value: 30.191374148543016
    - type: nAUC_P@100_std(MIRACL)
      value: 15.577217138606963
    - type: nAUC_P@10_diff1(MIRACL)
      value: -23.950963396253567
    - type: nAUC_P@10_max(MIRACL)
      value: 32.31620562041691
    - type: nAUC_P@10_std(MIRACL)
      value: 22.76652888514141
    - type: nAUC_P@1_diff1(MIRACL)
      value: 23.312659021070818
    - type: nAUC_P@1_max(MIRACL)
      value: 31.554119919664593
    - type: nAUC_P@1_std(MIRACL)
      value: 17.533789813864466
    - type: nAUC_P@20_diff1(MIRACL)
      value: -26.522109242426172
    - type: nAUC_P@20_max(MIRACL)
      value: 31.490097667881027
    - type: nAUC_P@20_std(MIRACL)
      value: 20.51757471839622
    - type: nAUC_P@3_diff1(MIRACL)
      value: -8.494670555442749
    - type: nAUC_P@3_max(MIRACL)
      value: 33.197306356212295
    - type: nAUC_P@3_std(MIRACL)
      value: 18.96447162170764
    - type: nAUC_P@5_diff1(MIRACL)
      value: -19.15325386641154
    - type: nAUC_P@5_max(MIRACL)
      value: 31.846463690427683
    - type: nAUC_P@5_std(MIRACL)
      value: 20.914296846825028
    - type: nAUC_Recall@1000_diff1(MIRACL)
      value: -22.62644777038629
    - type: nAUC_Recall@1000_max(MIRACL)
      value: 63.09417027858301
    - type: nAUC_Recall@1000_std(MIRACL)
      value: 31.96936126619333
    - type: nAUC_Recall@100_diff1(MIRACL)
      value: -22.62644777038629
    - type: nAUC_Recall@100_max(MIRACL)
      value: 63.09417027858301
    - type: nAUC_Recall@100_std(MIRACL)
      value: 31.96936126619333
    - type: nAUC_Recall@10_diff1(MIRACL)
      value: 1.389536667314163
    - type: nAUC_Recall@10_max(MIRACL)
      value: 36.80168430587649
    - type: nAUC_Recall@10_std(MIRACL)
      value: 24.6096121100626
    - type: nAUC_Recall@1_diff1(MIRACL)
      value: 37.50928508734578
    - type: nAUC_Recall@1_max(MIRACL)
      value: 13.158704351998995
    - type: nAUC_Recall@1_std(MIRACL)
      value: 4.422878276220556
    - type: nAUC_Recall@20_diff1(MIRACL)
      value: -8.586661617880036
    - type: nAUC_Recall@20_max(MIRACL)
      value: 48.977640900606715
    - type: nAUC_Recall@20_std(MIRACL)
      value: 30.787733282193763
    - type: nAUC_Recall@3_diff1(MIRACL)
      value: 20.85452801657472
    - type: nAUC_Recall@3_max(MIRACL)
      value: 20.457796008702196
    - type: nAUC_Recall@3_std(MIRACL)
      value: 10.422494162066547
    - type: nAUC_Recall@5_diff1(MIRACL)
      value: 11.294860119295114
    - type: nAUC_Recall@5_max(MIRACL)
      value: 24.55554040640634
    - type: nAUC_Recall@5_std(MIRACL)
      value: 15.07523755007524
  - task:
      type: Retrieval
    dataset:
      name: MTEB MIRACLRetrieval (ru)
      type: miracl/mmteb-miracl
      config: ru
      split: dev
      revision: main
    metrics:
    - type: main_score
      value: 53.33
    - type: map_at_1
      value: 23.51
    - type: map_at_10
      value: 42.506
    - type: map_at_100
      value: 45.727000000000004
    - type: map_at_1000
      value: 45.824
    - type: map_at_20
      value: 44.482
    - type: map_at_3
      value: 34.903
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  - task:
      type: Classification
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      type: mteb/amazon_massive_intent
      config: ru
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
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  - task:
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      type: mteb/amazon_massive_scenario
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      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
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  - task:
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      type: merionum/ru_paraphraser
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      revision: 43265056790b8f7c59e0139acb4be0a8dad2c8f4
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  - task:
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      type: ai-forever/ria-news-retrieval
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      revision: 82374b0bbacda6114f39ff9c5b925fa1512ca5d7
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    - type: ndcg_at_1000
      value: 79.252
    - type: ndcg_at_20
      value: 78.23400000000001
    - type: ndcg_at_3
      value: 74.36399999999999
    - type: ndcg_at_5
      value: 76.081
    - type: precision_at_1
      value: 64.92
    - type: precision_at_10
      value: 8.907
    - type: precision_at_100
      value: 0.9610000000000001
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_20
      value: 4.612
    - type: precision_at_3
      value: 26.933
    - type: precision_at_5
      value: 16.991999999999997
    - type: recall_at_1
      value: 64.92
    - type: recall_at_10
      value: 89.07000000000001
    - type: recall_at_100
      value: 96.14
    - type: recall_at_1000
      value: 98.39
    - type: recall_at_20
      value: 92.24
    - type: recall_at_3
      value: 80.80000000000001
    - type: recall_at_5
      value: 84.96000000000001
  - task:
      type: Reranking
    dataset:
      name: MTEB RuBQReranking
      type: ai-forever/rubq-reranking
      config: default
      split: test
      revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2
    metrics:
    - type: main_score
      value: 69.76660332457352
    - type: map
      value: 69.76660332457352
    - type: mrr
      value: 74.91840901415368
    - type: nAUC_map_diff1
      value: 40.77717577386574
    - type: nAUC_map_max
      value: 16.449821304849507
    - type: nAUC_map_std
      value: 5.464849678667512
    - type: nAUC_mrr_diff1
      value: 44.622323940651256
    - type: nAUC_mrr_max
      value: 20.915686008960645
    - type: nAUC_mrr_std
      value: 7.742740250688379
  - task:
      type: Retrieval
    dataset:
      name: MTEB RuBQRetrieval
      type: ai-forever/rubq-retrieval
      config: default
      split: test
      revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b
    metrics:
    - type: main_score
      value: 67.753
    - type: map_at_1
      value: 38.111
    - type: map_at_10
      value: 59.25
    - type: map_at_100
      value: 60.291
    - type: map_at_1000
      value: 60.31999999999999
    - type: map_at_20
      value: 60.007
    - type: map_at_3
      value: 53.39699999999999
    - type: map_at_5
      value: 57.021
    - type: mrr_at_1
      value: 54.60992907801418
    - type: mrr_at_10
      value: 67.53055930804169
    - type: mrr_at_100
      value: 67.88621490413858
    - type: mrr_at_1000
      value: 67.89435419716948
    - type: mrr_at_20
      value: 67.80457820326059
    - type: mrr_at_3
      value: 64.98226950354619
    - type: mrr_at_5
      value: 66.6991725768323
    - type: nauc_map_at_1000_diff1
      value: 38.61460560253499
    - type: nauc_map_at_1000_max
      value: 24.238741006152296
    - type: nauc_map_at_1000_std
      value: -12.553887111841771
    - type: nauc_map_at_100_diff1
      value: 38.604995328219836
    - type: nauc_map_at_100_max
      value: 24.25372744693149
    - type: nauc_map_at_100_std
      value: -12.525907529455832
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      value: 38.2802363146203
    - type: nauc_map_at_10_max
      value: 24.148397487087742
    - type: nauc_map_at_10_std
      value: -13.02462313254209
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      value: 42.20333973944006
    - type: nauc_map_at_1_max
      value: 16.04455015933995
    - type: nauc_map_at_1_std
      value: -11.426950122484298
    - type: nauc_map_at_20_diff1
      value: 38.49874303734095
    - type: nauc_map_at_20_max
      value: 24.27079948779279
    - type: nauc_map_at_20_std
      value: -12.643735833974782
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      value: 38.393442128336126
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      value: 21.120395203124264
    - type: nauc_map_at_3_std
      value: -14.57118408415527
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      value: 37.98874776320297
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      value: 22.75390581241078
    - type: nauc_map_at_5_std
      value: -13.871096120655116
    - type: nauc_mrr_at_1000_diff1
      value: 45.08121396075722
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      value: 27.331313499687486
    - type: nauc_mrr_at_1000_std
      value: -13.114787616167014
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      value: 45.082808269851654
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      value: 27.343021375586257
    - type: nauc_mrr_at_100_std
      value: -13.104901642101272
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      value: 44.89445664817906
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      value: 27.483504407572795
    - type: nauc_mrr_at_10_std
      value: -13.116664114214782
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      value: 47.43773937564259
    - type: nauc_mrr_at_1_max
      value: 24.3996512246477
    - type: nauc_mrr_at_1_std
      value: -13.283010969155859
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      value: 45.08382953390109
    - type: nauc_mrr_at_20_max
      value: 27.418666231602508
    - type: nauc_mrr_at_20_std
      value: -13.101239027782416
    - type: nauc_mrr_at_3_diff1
      value: 44.695558812456625
    - type: nauc_mrr_at_3_max
      value: 26.75153207261083
    - type: nauc_mrr_at_3_std
      value: -14.019251949468694
    - type: nauc_mrr_at_5_diff1
      value: 44.84929587390349
    - type: nauc_mrr_at_5_max
      value: 27.508337265101257
    - type: nauc_mrr_at_5_std
      value: -13.748841022127815
    - type: nauc_ndcg_at_1000_diff1
      value: 39.706451835474724
    - type: nauc_ndcg_at_1000_max
      value: 26.633343785995507
    - type: nauc_ndcg_at_1000_std
      value: -11.207900377782707
    - type: nauc_ndcg_at_100_diff1
      value: 39.49574863029789
    - type: nauc_ndcg_at_100_max
      value: 27.03615356082193
    - type: nauc_ndcg_at_100_std
      value: -10.456416625790485
    - type: nauc_ndcg_at_10_diff1
      value: 38.36118560524438
    - type: nauc_ndcg_at_10_max
      value: 27.29115954765498
    - type: nauc_ndcg_at_10_std
      value: -12.026533782516182
    - type: nauc_ndcg_at_1_diff1
      value: 47.43773937564259
    - type: nauc_ndcg_at_1_max
      value: 24.3996512246477
    - type: nauc_ndcg_at_1_std
      value: -13.283010969155859
    - type: nauc_ndcg_at_20_diff1
      value: 39.11328986667616
    - type: nauc_ndcg_at_20_max
      value: 27.48803343585931
    - type: nauc_ndcg_at_20_std
      value: -11.061481936299867
    - type: nauc_ndcg_at_3_diff1
      value: 38.09080511583124
    - type: nauc_ndcg_at_3_max
      value: 22.960624575385577
    - type: nauc_ndcg_at_3_std
      value: -15.162532187246452
    - type: nauc_ndcg_at_5_diff1
      value: 37.84051905054443
    - type: nauc_ndcg_at_5_max
      value: 24.859831442018766
    - type: nauc_ndcg_at_5_std
      value: -14.208813731290032
    - type: nauc_precision_at_1000_diff1
      value: -8.235293550747457
    - type: nauc_precision_at_1000_max
      value: 7.564714965839937
    - type: nauc_precision_at_1000_std
      value: 5.160867910754626
    - type: nauc_precision_at_100_diff1
      value: -6.654255562369982
    - type: nauc_precision_at_100_max
      value: 10.671679751630798
    - type: nauc_precision_at_100_std
      value: 7.057997024307852
    - type: nauc_precision_at_10_diff1
      value: 0.4759476932076396
    - type: nauc_precision_at_10_max
      value: 18.705407595194696
    - type: nauc_precision_at_10_std
      value: 1.1284269201001864
    - type: nauc_precision_at_1_diff1
      value: 47.43773937564259
    - type: nauc_precision_at_1_max
      value: 24.3996512246477
    - type: nauc_precision_at_1_std
      value: -13.283010969155859
    - type: nauc_precision_at_20_diff1
      value: -3.1830019504133027
    - type: nauc_precision_at_20_max
      value: 15.311012950383418
    - type: nauc_precision_at_20_std
      value: 4.411311445012971
    - type: nauc_precision_at_3_diff1
      value: 14.900799832530298
    - type: nauc_precision_at_3_max
      value: 21.59448854239842
    - type: nauc_precision_at_3_std
      value: -10.383301518031464
    - type: nauc_precision_at_5_diff1
      value: 6.129583634729085
    - type: nauc_precision_at_5_max
      value: 19.764705099171525
    - type: nauc_precision_at_5_std
      value: -4.931119926816597
    - type: nauc_recall_at_1000_diff1
      value: 7.393009712112532
    - type: nauc_recall_at_1000_max
      value: 49.79443106358621
    - type: nauc_recall_at_1000_std
      value: 74.80255240755591
    - type: nauc_recall_at_100_diff1
      value: 19.35257139711146
    - type: nauc_recall_at_100_max
      value: 42.80851742013903
    - type: nauc_recall_at_100_std
      value: 37.546560048377444
    - type: nauc_recall_at_10_diff1
      value: 24.621169385136398
    - type: nauc_recall_at_10_max
      value: 33.22268204638332
    - type: nauc_recall_at_10_std
      value: -4.7401788730268235
    - type: nauc_recall_at_1_diff1
      value: 42.20333973944006
    - type: nauc_recall_at_1_max
      value: 16.04455015933995
    - type: nauc_recall_at_1_std
      value: -11.426950122484298
    - type: nauc_recall_at_20_diff1
      value: 24.927652532242657
    - type: nauc_recall_at_20_max
      value: 38.260344944664766
    - type: nauc_recall_at_20_std
      value: 5.423281114042867
    - type: nauc_recall_at_3_diff1
      value: 30.44227595912427
    - type: nauc_recall_at_3_max
      value: 19.94976153694003
    - type: nauc_recall_at_3_std
      value: -15.928733556196534
    - type: nauc_recall_at_5_diff1
      value: 27.044814357935724
    - type: nauc_recall_at_5_max
      value: 23.824668491154366
    - type: nauc_recall_at_5_std
      value: -13.992845356113314
    - type: ndcg_at_1
      value: 54.61
    - type: ndcg_at_10
      value: 67.753
    - type: ndcg_at_100
      value: 70.926
    - type: ndcg_at_1000
      value: 71.41
    - type: ndcg_at_20
      value: 69.61500000000001
    - type: ndcg_at_3
      value: 59.678
    - type: ndcg_at_5
      value: 64.012
    - type: precision_at_1
      value: 54.61
    - type: precision_at_10
      value: 13.747000000000002
    - type: precision_at_100
      value: 1.601
    - type: precision_at_1000
      value: 0.166
    - type: precision_at_20
      value: 7.446999999999999
    - type: precision_at_3
      value: 33.255
    - type: precision_at_5
      value: 23.747
    - type: recall_at_1
      value: 38.111
    - type: recall_at_10
      value: 83.878
    - type: recall_at_100
      value: 95.84899999999999
    - type: recall_at_1000
      value: 99.05199999999999
    - type: recall_at_20
      value: 90.048
    - type: recall_at_3
      value: 64.126
    - type: recall_at_5
      value: 74.295
  - task:
      type: Classification
    dataset:
      name: MTEB RuReviewsClassification
      type: ai-forever/ru-reviews-classification
      config: default
      split: test
      revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a
    metrics:
    - type: accuracy
      value: 66.0888671875
    - type: f1
      value: 63.79342584872498
    - type: f1_weighted
      value: 63.79112620928187
    - type: main_score
      value: 66.0888671875
  - task:
      type: STS
    dataset:
      name: MTEB RuSTSBenchmarkSTS
      type: ai-forever/ru-stsbenchmark-sts
      config: default
      split: test
      revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018
    metrics:
    - type: cosine_pearson
      value: 78.40381860532754
    - type: cosine_spearman
      value: 78.44128247246344
    - type: euclidean_pearson
      value: 77.03436669125563
    - type: euclidean_spearman
      value: 78.44009017152538
    - type: main_score
      value: 78.44128247246344
    - type: manhattan_pearson
      value: 77.084766201637
    - type: manhattan_spearman
      value: 78.46899044600028
    - type: pearson
      value: 78.40381860532754
    - type: spearman
      value: 78.44128247246344
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchGRNTIClassification
      type: ai-forever/ru-scibench-grnti-classification
      config: default
      split: test
      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
    metrics:
    - type: accuracy
      value: 61.4111328125
    - type: f1
      value: 59.604229603854044
    - type: f1_weighted
      value: 59.61906710038802
    - type: main_score
      value: 61.4111328125
  - task:
      type: Clustering
    dataset:
      name: MTEB RuSciBenchGRNTIClusteringP2P
      type: ai-forever/ru-scibench-grnti-classification
      config: default
      split: test
      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
    metrics:
    - type: main_score
      value: 55.660781672610625
    - type: v_measure
      value: 55.660781672610625
    - type: v_measure_std
      value: 1.0880487214373578
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchOECDClassification
      type: ai-forever/ru-scibench-oecd-classification
      config: default
      split: test
      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
    metrics:
    - type: accuracy
      value: 48.6669921875
    - type: f1
      value: 46.24529719568694
    - type: f1_weighted
      value: 46.24736172369365
    - type: main_score
      value: 48.6669921875
  - task:
      type: Clustering
    dataset:
      name: MTEB RuSciBenchOECDClusteringP2P
      type: ai-forever/ru-scibench-oecd-classification
      config: default
      split: test
      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
    metrics:
    - type: main_score
      value: 47.95513383500326
    - type: v_measure
      value: 47.95513383500326
    - type: v_measure_std
      value: 0.9391146092620886
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 65.27471390704719
    - type: cosine_spearman
      value: 68.12010913287949
    - type: euclidean_pearson
      value: 65.60124415285192
    - type: euclidean_spearman
      value: 68.12010913287949
    - type: main_score
      value: 68.12010913287949
    - type: manhattan_pearson
      value: 65.21850751060232
    - type: manhattan_spearman
      value: 67.85162022914248
    - type: pearson
      value: 65.27471390704719
    - type: spearman
      value: 68.12010913287949
  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB SensitiveTopicsClassification
      type: ai-forever/sensitive-topics-classification
      config: default
      split: test
      revision: 416b34a802308eac30e4192afc0ff99bb8dcc7f2
    metrics:
    - type: accuracy
      value: 30.0537109375
    - type: f1
      value: 35.12028781898003
    - type: lrap
      value: 45.91071234808953
    - type: main_score
      value: 30.0537109375
  - task:
      type: PairClassification
    dataset:
      name: MTEB TERRa
      type: ai-forever/terra-pairclassification
      config: default
      split: dev
      revision: 7b58f24536063837d644aab9a023c62199b2a612
    metrics:
    - type: cosine_accuracy
      value: 60.91205211726385
    - type: cosine_accuracy_threshold
      value: 68.15387606620789
    - type: cosine_ap
      value: 57.705995373862805
    - type: cosine_f1
      value: 67.57990867579909
    - type: cosine_f1_threshold
      value: 54.87680435180664
    - type: cosine_precision
      value: 51.92982456140351
    - type: cosine_recall
      value: 96.73202614379085
    - type: dot_accuracy
      value: 60.91205211726385
    - type: dot_accuracy_threshold
      value: 68.15387010574341
    - type: dot_ap
      value: 57.705995373862805
    - type: dot_f1
      value: 67.57990867579909
    - type: dot_f1_threshold
      value: 54.87680435180664
    - type: dot_precision
      value: 51.92982456140351
    - type: dot_recall
      value: 96.73202614379085
    - type: euclidean_accuracy
      value: 60.91205211726385
    - type: euclidean_accuracy_threshold
      value: 79.80742454528809
    - type: euclidean_ap
      value: 57.705995373862805
    - type: euclidean_f1
      value: 67.57990867579909
    - type: euclidean_f1_threshold
      value: 94.99809741973877
    - type: euclidean_precision
      value: 51.92982456140351
    - type: euclidean_recall
      value: 96.73202614379085
    - type: main_score
      value: 57.705995373862805
    - type: manhattan_accuracy
      value: 60.586319218241044
    - type: manhattan_accuracy_threshold
      value: 1858.333969116211
    - type: manhattan_ap
      value: 57.53277048517774
    - type: manhattan_f1
      value: 67.59259259259261
    - type: manhattan_f1_threshold
      value: 2154.4769287109375
    - type: manhattan_precision
      value: 52.32974910394266
    - type: manhattan_recall
      value: 95.42483660130719
    - type: max_ap
      value: 57.705995373862805
    - type: max_f1
      value: 67.59259259259261
    - type: max_precision
      value: 52.32974910394266
    - type: max_recall
      value: 96.73202614379085
    - type: similarity_accuracy
      value: 60.91205211726385
    - type: similarity_accuracy_threshold
      value: 68.15387606620789
    - type: similarity_ap
      value: 57.705995373862805
    - type: similarity_f1
      value: 67.57990867579909
    - type: similarity_f1_threshold
      value: 54.87680435180664
    - type: similarity_precision
      value: 51.92982456140351
    - type: similarity_recall
      value: 96.73202614379085
---
-

<h1 align="center">KaLM-Embedding</h1>


**KaLM-Embedding** is a series of embedding models adapted from auto-regressive LLMs with superior training data.

KaLM-embedding-multilingual-mini is trained from [Qwen/Qwen2-0.5B](https://huggingface.co/Qwen/Qwen2-0.5B) with massive weakly-supervised pre-training and supervised fine-tuning data.


## 📑 Open-source Plan

- [x] Model Checkpoint 
    - [x] [KaLM-embedding-multilingual-mini-v1](https://huggingface.co/HIT-TMG/KaLM-embedding-multilingual-mini-v1)
    - [x] [KaLM-embedding-multilingual-mini-instruct-v1](https://huggingface.co/HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1)
    - [x] [KaLM-embedding-multilingual-mini-instruct-v1.5](https://huggingface.co/HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5)
    - [ ] KaLM-embedding-multilingual-max-v1
- [x] Training and Evaluation Code: [HITsz-TMG/KaLM-Embedding](https://github.com/HITsz-TMG/KaLM-Embedding)
- [x] Technical Report: [KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model](https://arxiv.org/abs/2501.01028)
- [ ] Training Data


## Evaluation

 | Model Name | Model Size | C-MTEB(35) | MTEB(56) | avg
|:----:|:---:|:---:|:---:|:---:| 
| [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) | 560M | 58.81 | 61.5 | 60.16
| [bge-m3 (dense)](https://huggingface.co/BAAI/bge-m3) | 560M | 60.80 | 59.84 | 60.32
| [gte-multilingual-base (dense)](https://huggingface.co/Alibaba-NLP/gte-multilingual-base) | **305M** | 62.72 | 61.40 | 62.06 
| [KaLM-embedding-multilingual-mini-v1](https://huggingface.co/HIT-TMG/KaLM-embedding-multilingual-mini-v1) | 494M | 62.31 | 61.87 | 62.09
| [KaLM-embedding-multilingual-mini-instruct-v1](https://huggingface.co/HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1) | 494M | 63.57 | 64.74 | 64.16
| [KaLM-embedding-multilingual-mini-instruct-v1.5](https://huggingface.co/HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5) | 494M | **64.13** | **64.94** | **64.53**



## Requirements
Since we have used the Qwen2 model, we advise you to install `transformers>=4.37.0`, or you might encounter the following error:
```
KeyError: 'qwen2'
```


## Usage

Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

```python
from sentence_transformers import SentenceTransformer


sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('{MODEL_NAME_OR_PATH}')   # Do NOT set trust_remote_code
model.max_seq_length = 512

embeddings = model.encode(
    sentences, 
    normalize_embeddings=True,
    batch_size=256, 
    show_progress_bar=True
    )
print(embeddings)
```

<!-- We add instruction for asymmetric tasks: retrieval, reranking, classification and clustering. -->
We add instruction for classification and clustering.
If you want to add instruction to the query (no instruction for the corpus), you can use the model like this:

```python
from sentence_transformers import SentenceTransformer


sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('{MODEL_NAME_OR_PATH}')   # Do NOT set trust_remote_code
model.max_seq_length = 512

prompt = "Instruct: Classifying the category of french news. \n Query: "
embeddings = model.encode(
    sentences, 
    prompt=prompt,
    normalize_embeddings=True,
    batch_size=256, 
    show_progress_bar=True
    )
print(embeddings)
```


## Contact
If you encounter any issue, feel free to contact us via the email: yanshek.woo@gmail.com
