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: 94.68515742128936
    - type: ap
      value: 61.63091951041035
    - type: ap_weighted
      value: 61.63091951041035
    - type: f1
      value: 87.0707144798333
    - type: f1_weighted
      value: 94.92507672044346
    - type: main_score
      value: 94.68515742128936
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 91.73134328358209
    - type: ap
      value: 68.35026743834399
    - type: ap_weighted
      value: 68.35026743834399
    - type: f1
      value: 87.90511074439425
    - type: f1_weighted
      value: 92.04737679749206
    - type: main_score
      value: 91.73134328358209
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 96.55665
    - type: ap
      value: 95.07549068622335
    - type: ap_weighted
      value: 95.07549068622335
    - type: f1
      value: 96.55609959481485
    - type: f1_weighted
      value: 96.55609959481488
    - type: main_score
      value: 96.55665
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 61.42000000000001
    - type: f1
      value: 59.435009609195
    - type: f1_weighted
      value: 59.435009609195
    - type: main_score
      value: 61.42000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
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    - type: map_at_10
      value: 49.632
    - type: map_at_100
      value: 50.33800000000001
    - type: map_at_1000
      value: 50.341
    - type: map_at_20
      value: 50.224000000000004
    - type: map_at_3
      value: 44.832
    - type: map_at_5
      value: 47.620000000000005
    - type: mrr_at_1
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    - type: mrr_at_10
      value: 49.811380929802155
    - 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_5
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    - type: ndcg_at_100
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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: recall_at_1
      value: 33.073
    - type: recall_at_10
      value: 87.26899999999999
    - type: recall_at_100
      value: 99.14699999999999
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_20
      value: 95.377
    - type: recall_at_3
      value: 60.028000000000006
    - type: recall_at_5
      value: 72.404
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: main_score
      value: 49.682199850672866
    - type: v_measure
      value: 49.682199850672866
    - type: v_measure_std
      value: 14.233482745120106
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: main_score
      value: 42.209464702274715
    - type: v_measure
      value: 42.209464702274715
    - type: v_measure_std
      value: 14.710188553304171
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: main_score
      value: 60.34670620892353
    - type: map
      value: 60.34670620892353
    - type: mrr
      value: 74.21360418590336
    - type: nAUC_map_diff1
      value: 11.911350612613562
    - type: nAUC_map_max
      value: 16.783478049340925
    - type: nAUC_map_std
      value: 16.428460426761752
    - type: nAUC_mrr_diff1
      value: 14.989972807815782
    - type: nAUC_mrr_max
      value: 25.277551101334105
    - type: nAUC_mrr_std
      value: 16.506353229551408
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cosine_pearson
      value: 88.03646117514994
    - type: cosine_spearman
      value: 86.1423242570783
    - type: euclidean_pearson
      value: 87.25661641211398
    - type: euclidean_spearman
      value: 86.1423242570783
    - type: main_score
      value: 86.1423242570783
    - type: manhattan_pearson
      value: 86.75341029385434
    - type: manhattan_spearman
      value: 85.43447680299268
    - type: pearson
      value: 88.03646117514994
    - type: spearman
      value: 86.1423242570783
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 84.54220779220778
    - type: f1
      value: 83.93093828135092
    - type: f1_weighted
      value: 83.9309382813509
    - type: main_score
      value: 84.54220779220778
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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      value: 43.84044619752363
    - type: v_measure
      value: 43.84044619752363
    - type: v_measure_std
      value: 0.4618669625794188
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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      value: 37.31116089915042
    - type: v_measure
      value: 37.31116089915042
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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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      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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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
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      value: 85.75923392612859
  - 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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      value: 79.32414256893072
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
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  - task:
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      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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    - type: v_measure
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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:
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      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
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  - task:
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  - task:
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  - task:
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  - task:
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      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cosine_pearson
      value: 83.80746802573121
    - type: cosine_spearman
      value: 79.72822038569593
    - type: euclidean_pearson
      value: 81.45002980681224
    - type: euclidean_spearman
      value: 79.7282231441618
    - type: main_score
      value: 79.72822038569593
    - type: manhattan_pearson
      value: 81.45611398621358
    - type: manhattan_spearman
      value: 79.59811193829754
    - type: pearson
      value: 83.80746802573121
    - type: spearman
      value: 79.72822038569593
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cosine_pearson
      value: 87.3063084337013
    - type: cosine_spearman
      value: 80.16653334500153
    - type: euclidean_pearson
      value: 84.24369437820418
    - type: euclidean_spearman
      value: 80.16592228280822
    - type: main_score
      value: 80.16653334500153
    - type: manhattan_pearson
      value: 84.41598625996673
    - type: manhattan_spearman
      value: 80.37993757607657
    - type: pearson
      value: 87.3063084337013
    - type: spearman
      value: 80.16653334500153
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cosine_pearson
      value: 82.56917286956067
    - type: cosine_spearman
      value: 83.86019247474584
    - type: euclidean_pearson
      value: 83.50577094515269
    - type: euclidean_spearman
      value: 83.86019240020342
    - type: main_score
      value: 83.86019247474584
    - type: manhattan_pearson
      value: 83.7035831723258
    - type: manhattan_spearman
      value: 84.06951592208223
    - type: pearson
      value: 82.56917286956067
    - type: spearman
      value: 83.86019247474584
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cosine_pearson
      value: 82.57349080713945
    - type: cosine_spearman
      value: 80.5656376543151
    - type: euclidean_pearson
      value: 82.20020711843652
    - type: euclidean_spearman
      value: 80.56562435929797
    - type: main_score
      value: 80.5656376543151
    - type: manhattan_pearson
      value: 82.02137444105155
    - type: manhattan_spearman
      value: 80.49473867409459
    - type: pearson
      value: 82.57349080713945
    - type: spearman
      value: 80.5656376543151
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cosine_pearson
      value: 85.89932616809199
    - type: cosine_spearman
      value: 87.34265089376507
    - type: euclidean_pearson
      value: 86.70361638349567
    - type: euclidean_spearman
      value: 87.34265218193244
    - type: main_score
      value: 87.34265089376507
    - type: manhattan_pearson
      value: 86.51826134790748
    - type: manhattan_spearman
      value: 87.18812519859725
    - type: pearson
      value: 85.89932616809199
    - type: spearman
      value: 87.34265089376507
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cosine_pearson
      value: 83.57539157713117
    - type: cosine_spearman
      value: 84.8327592322146
    - type: euclidean_pearson
      value: 84.04928896411587
    - type: euclidean_spearman
      value: 84.83275862198806
    - type: main_score
      value: 84.8327592322146
    - type: manhattan_pearson
      value: 83.88919473293718
    - type: manhattan_spearman
      value: 84.64175696279177
    - type: pearson
      value: 83.57539157713117
    - type: spearman
      value: 84.8327592322146
  - 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: 56.77939191972398
    - type: cosine_spearman
      value: 56.44421451336106
    - type: euclidean_pearson
      value: 57.84746999725719
    - type: euclidean_spearman
      value: 56.44421451336106
    - type: main_score
      value: 56.44421451336106
    - type: manhattan_pearson
      value: 56.368375736935185
    - type: manhattan_spearman
      value: 54.443033747967476
    - type: pearson
      value: 56.77939191972398
    - type: spearman
      value: 56.44421451336106
  - 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: 72.7123285460032
    - type: cosine_spearman
      value: 73.0413412902408
    - type: euclidean_pearson
      value: 73.26576109213129
    - type: euclidean_spearman
      value: 73.0413412902408
    - type: main_score
      value: 73.0413412902408
    - type: manhattan_pearson
      value: 73.18845328161191
    - type: manhattan_spearman
      value: 73.01804685924571
    - type: pearson
      value: 72.7123285460032
    - type: spearman
      value: 73.0413412902408
  - 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: 85.76937213938014
    - type: cosine_spearman
      value: 86.42806650035523
    - type: euclidean_pearson
      value: 86.6429129637805
    - type: euclidean_spearman
      value: 86.42806650035523
    - type: main_score
      value: 86.42806650035523
    - type: manhattan_pearson
      value: 86.57962956067654
    - type: manhattan_spearman
      value: 86.18220646628836
    - type: pearson
      value: 85.76937213938014
    - type: spearman
      value: 86.42806650035523
  - 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: 53.63838562350928
    - type: cosine_spearman
      value: 51.425433307585536
    - type: euclidean_pearson
      value: 53.89159715974961
    - type: euclidean_spearman
      value: 51.425433307585536
    - type: main_score
      value: 51.425433307585536
    - type: manhattan_pearson
      value: 53.072978089852526
    - type: manhattan_spearman
      value: 50.42207979849882
    - type: pearson
      value: 53.63838562350928
    - type: spearman
      value: 51.425433307585536
  - 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: 74.86829926679785
    - type: cosine_spearman
      value: 75.97371995137269
    - type: euclidean_pearson
      value: 75.31029737838625
    - type: euclidean_spearman
      value: 75.97371995137269
    - type: main_score
      value: 75.97371995137269
    - type: manhattan_pearson
      value: 75.65839894637686
    - type: manhattan_spearman
      value: 76.1355272163419
    - type: pearson
      value: 74.86829926679785
    - type: spearman
      value: 75.97371995137269
  - 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: 74.71447286299487
    - type: cosine_spearman
      value: 74.06702660747132
    - type: euclidean_pearson
      value: 75.38807553614491
    - type: euclidean_spearman
      value: 74.06702660747132
    - type: main_score
      value: 74.06702660747132
    - type: manhattan_pearson
      value: 75.12369492510138
    - type: manhattan_spearman
      value: 73.91369082324793
    - type: pearson
      value: 74.71447286299487
    - type: spearman
      value: 74.06702660747132
  - 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: 72.38044871568002
    - type: cosine_spearman
      value: 72.67462698051628
    - type: euclidean_pearson
      value: 72.93088753362804
    - type: euclidean_spearman
      value: 72.67462698051628
    - type: main_score
      value: 72.67462698051628
    - type: manhattan_pearson
      value: 72.36507526375641
    - type: manhattan_spearman
      value: 72.05743987811199
    - type: pearson
      value: 72.38044871568002
    - type: spearman
      value: 72.67462698051628
  - 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: 70.21041932205698
    - type: cosine_spearman
      value: 69.70028178727163
    - type: euclidean_pearson
      value: 70.90563853073118
    - type: euclidean_spearman
      value: 69.70028178727163
    - type: main_score
      value: 69.70028178727163
    - type: manhattan_pearson
      value: 70.57814054683753
    - type: manhattan_spearman
      value: 69.09462658139957
    - type: pearson
      value: 70.21041932205698
    - type: spearman
      value: 69.70028178727163
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 69.13900601047764
    - type: cosine_spearman
      value: 69.2134140940147
    - type: euclidean_pearson
      value: 70.74438767160798
    - type: euclidean_spearman
      value: 69.2134140940147
    - type: main_score
      value: 69.2134140940147
    - type: manhattan_pearson
      value: 71.02398307661159
    - type: manhattan_spearman
      value: 69.37936110586129
    - type: pearson
      value: 69.13900601047764
    - type: spearman
      value: 69.2134140940147
  - 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: 64.8805006605935
    - type: cosine_spearman
      value: 63.81067904946749
    - type: euclidean_pearson
      value: 67.42954643546759
    - type: euclidean_spearman
      value: 63.81067904946749
    - type: main_score
      value: 63.81067904946749
    - type: manhattan_pearson
      value: 68.5718639745086
    - type: manhattan_spearman
      value: 64.77027566921338
    - type: pearson
      value: 64.8805006605935
    - type: spearman
      value: 63.81067904946749
  - 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: 75.50011820404733
    - type: cosine_spearman
      value: 78.22942242197527
    - type: euclidean_pearson
      value: 76.7001402354704
    - type: euclidean_spearman
      value: 78.22942242197527
    - type: main_score
      value: 78.22942242197527
    - type: manhattan_pearson
      value: 78.77879852950737
    - type: manhattan_spearman
      value: 79.58485702006229
    - type: pearson
      value: 75.50011820404733
    - type: spearman
      value: 78.22942242197527
  - 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: 78.98435260035146
    - type: cosine_spearman
      value: 79.0083835281799
    - type: euclidean_pearson
      value: 79.05051294275746
    - type: euclidean_spearman
      value: 79.0083835281799
    - type: main_score
      value: 79.0083835281799
    - type: manhattan_pearson
      value: 79.28546319449809
    - type: manhattan_spearman
      value: 78.79790129500051
    - type: pearson
      value: 78.98435260035146
    - type: spearman
      value: 79.0083835281799
    - type: cosine_pearson
      value: 78.98435260035146
    - type: cosine_spearman
      value: 79.0083835281799
    - type: euclidean_pearson
      value: 79.05051294275746
    - type: euclidean_spearman
      value: 79.0083835281799
    - type: main_score
      value: 79.0083835281799
    - type: manhattan_pearson
      value: 79.28546319449809
    - type: manhattan_spearman
      value: 78.79790129500051
    - type: pearson
      value: 78.98435260035146
    - type: spearman
      value: 79.0083835281799
  - 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: 76.5491270627292
    - type: cosine_spearman
      value: 76.34747339191613
    - type: euclidean_pearson
      value: 77.52703884917828
    - type: euclidean_spearman
      value: 76.34747339191613
    - type: main_score
      value: 76.34747339191613
    - type: manhattan_pearson
      value: 77.94417346436772
    - type: manhattan_spearman
      value: 76.15552728253843
    - type: pearson
      value: 76.5491270627292
    - type: spearman
      value: 76.34747339191613
    - type: cosine_pearson
      value: 76.5491270627292
    - type: cosine_spearman
      value: 76.34747339191613
    - type: euclidean_pearson
      value: 77.52703884917828
    - type: euclidean_spearman
      value: 76.34747339191613
    - type: main_score
      value: 76.34747339191613
    - type: manhattan_pearson
      value: 77.94417346436772
    - type: manhattan_spearman
      value: 76.15552728253843
    - type: pearson
      value: 76.5491270627292
    - type: spearman
      value: 76.34747339191613
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cosine_pearson
      value: 81.44263012519023
    - type: cosine_spearman
      value: 84.1219543406234
    - type: euclidean_pearson
      value: 83.61379006230743
    - type: euclidean_spearman
      value: 84.1219543406234
    - type: main_score
      value: 84.1219543406234
    - type: manhattan_pearson
      value: 83.40336227949633
    - type: manhattan_spearman
      value: 83.94639826019986
    - type: pearson
      value: 81.44263012519023
    - type: spearman
      value: 84.1219543406234
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: main_score
      value: 80.99314184170828
    - type: map
      value: 80.99314184170828
    - type: mrr
      value: 94.80081918807409
    - type: nAUC_map_diff1
      value: 2.519316498883737
    - type: nAUC_map_max
      value: 53.83115362914741
    - type: nAUC_map_std
      value: 71.18884208143534
    - type: nAUC_mrr_diff1
      value: 49.13813585315955
    - type: nAUC_mrr_max
      value: 82.97821200827201
    - type: nAUC_mrr_std
      value: 80.52851378034694
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: main_score
      value: 72.887
    - type: map_at_1
      value: 56.983
    - type: map_at_10
      value: 68.02
    - type: map_at_100
      value: 68.47800000000001
    - type: map_at_1000
      value: 68.49300000000001
    - type: map_at_20
      value: 68.319
    - type: map_at_3
      value: 64.735
    - type: map_at_5
      value: 66.797
    - type: mrr_at_1
      value: 60.0
    - type: mrr_at_10
      value: 68.80674603174603
    - type: mrr_at_100
      value: 69.17683357934396
    - type: mrr_at_1000
      value: 69.19182270659053
    - type: mrr_at_20
      value: 69.04443591467584
    - type: mrr_at_3
      value: 66.22222222222221
    - type: mrr_at_5
      value: 67.88888888888889
    - type: nauc_map_at_1000_diff1
      value: 65.74751339600985
    - type: nauc_map_at_1000_max
      value: 51.01631394192724
    - type: nauc_map_at_1000_std
      value: -4.749077682272638
    - type: nauc_map_at_100_diff1
      value: 65.7511025839809
    - type: nauc_map_at_100_max
      value: 51.02179965776254
    - type: nauc_map_at_100_std
      value: -4.750648691834171
    - type: nauc_map_at_10_diff1
      value: 65.8078854827133
    - type: nauc_map_at_10_max
      value: 51.17250624028733
    - type: nauc_map_at_10_std
      value: -5.145740047184135
    - type: nauc_map_at_1_diff1
      value: 69.1712101533685
    - type: nauc_map_at_1_max
      value: 46.030719621812224
    - type: nauc_map_at_1_std
      value: -8.492699133614764
    - type: nauc_map_at_20_diff1
      value: 65.72860985168403
    - type: nauc_map_at_20_max
      value: 51.02243609996885
    - type: nauc_map_at_20_std
      value: -4.897680708725447
    - type: nauc_map_at_3_diff1
      value: 66.04795347641515
    - type: nauc_map_at_3_max
      value: 49.28417356777598
    - type: nauc_map_at_3_std
      value: -8.144355960324793
    - type: nauc_map_at_5_diff1
      value: 65.39564471101812
    - type: nauc_map_at_5_max
      value: 49.8786868247306
    - type: nauc_map_at_5_std
      value: -5.361632284686927
    - type: nauc_mrr_at_1000_diff1
      value: 65.35483966038701
    - type: nauc_mrr_at_1000_max
      value: 52.46038918168655
    - type: nauc_mrr_at_1000_std
      value: -2.9488525087661865
    - type: nauc_mrr_at_100_diff1
      value: 65.35869633533838
    - type: nauc_mrr_at_100_max
      value: 52.465078488348915
    - type: nauc_mrr_at_100_std
      value: -2.9515006369786185
    - type: nauc_mrr_at_10_diff1
      value: 65.32937085681456
    - type: nauc_mrr_at_10_max
      value: 52.69576591011457
    - type: nauc_mrr_at_10_std
      value: -3.211748975877107
    - type: nauc_mrr_at_1_diff1
      value: 68.74146631047786
    - type: nauc_mrr_at_1_max
      value: 50.13505491243696
    - type: nauc_mrr_at_1_std
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    - type: nauc_mrr_at_20_diff1
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  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
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      value: 66.37519604053632
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  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
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    - type: v_measure
      value: 39.19275669318283
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      value: 1.433472639700171
  - task:
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    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
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  - task:
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      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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  - task:
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      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
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    - type: ndcg_at_100
      value: 66.322
    - type: ndcg_at_1000
      value: 58.794000000000004
    - type: ndcg_at_20
      value: 81.339
    - type: ndcg_at_3
      value: 86.827
    - type: ndcg_at_5
      value: 85.372
    - type: precision_at_1
      value: 88.0
    - type: precision_at_10
      value: 88.4
    - type: precision_at_100
      value: 68.89999999999999
    - type: precision_at_1000
      value: 25.913999999999998
    - type: precision_at_20
      value: 86.0
    - type: precision_at_3
      value: 92.0
    - type: precision_at_5
      value: 90.8
    - type: recall_at_1
      value: 0.22499999999999998
    - type: recall_at_10
      value: 2.3120000000000003
    - type: recall_at_100
      value: 16.84
    - type: recall_at_1000
      value: 55.541
    - type: recall_at_20
      value: 4.478
    - type: recall_at_3
      value: 0.735
    - type: recall_at_5
      value: 1.188
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: main_score
      value: 29.148000000000003
    - type: map_at_1
      value: 2.9690000000000003
    - type: map_at_10
      value: 12.183
    - type: map_at_100
      value: 18.934
    - type: map_at_1000
      value: 20.657
    - type: map_at_20
      value: 14.995
    - type: map_at_3
      value: 6.261
    - type: map_at_5
      value: 8.463
    - type: mrr_at_1
      value: 40.816326530612244
    - type: mrr_at_10
      value: 54.33916423712341
    - type: mrr_at_100
      value: 55.424228921812166
    - type: mrr_at_1000
      value: 55.424228921812166
    - type: mrr_at_20
      value: 55.115252184263994
    - type: mrr_at_3
      value: 51.360544217687064
    - type: mrr_at_5
      value: 53.707482993197274
    - type: nauc_map_at_1000_diff1
      value: 24.39650474897996
    - type: nauc_map_at_1000_max
      value: -24.9951891255025
    - type: nauc_map_at_1000_std
      value: 9.605455246028367
    - type: nauc_map_at_100_diff1
      value: 25.536859954016666
    - type: nauc_map_at_100_max
      value: -25.804629962474262
    - type: nauc_map_at_100_std
      value: 6.269656637665734
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      value: 24.85518759986692
    - type: nauc_map_at_10_max
      value: -23.813502179044356
    - type: nauc_map_at_10_std
      value: -10.511927624839066
    - type: nauc_map_at_1_diff1
      value: 38.988840017170084
    - type: nauc_map_at_1_max
      value: -32.91111385240854
    - type: nauc_map_at_1_std
      value: -23.593390331872705
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      value: 21.90593939858651
    - type: nauc_map_at_20_max
      value: -23.88012227409119
    - type: nauc_map_at_20_std
      value: -5.8228272625717965
    - type: nauc_map_at_3_diff1
      value: 32.30334028131513
    - type: nauc_map_at_3_max
      value: -37.94218032778254
    - type: nauc_map_at_3_std
      value: -20.73094293061375
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      value: 22.700908074741232
    - type: nauc_map_at_5_max
      value: -29.289350038869493
    - type: nauc_map_at_5_std
      value: -15.465462985852394
    - type: nauc_mrr_at_1000_diff1
      value: 36.35450280091282
    - type: nauc_mrr_at_1000_max
      value: -46.85388076847817
    - type: nauc_mrr_at_1000_std
      value: -11.371621140495272
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      value: 36.35450280091282
    - type: nauc_mrr_at_100_max
      value: -46.85388076847817
    - type: nauc_mrr_at_100_std
      value: -11.371621140495272
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      value: 36.49601491862039
    - type: nauc_mrr_at_10_max
      value: -48.23156353834522
    - type: nauc_mrr_at_10_std
      value: -10.235106950548067
    - type: nauc_mrr_at_1_diff1
      value: 30.580995175260696
    - type: nauc_mrr_at_1_max
      value: -41.150802011358095
    - type: nauc_mrr_at_1_std
      value: -18.734158460340613
    - type: nauc_mrr_at_20_diff1
      value: 36.71852563079837
    - type: nauc_mrr_at_20_max
      value: -47.057569621975745
    - type: nauc_mrr_at_20_std
      value: -10.6425202175546
    - type: nauc_mrr_at_3_diff1
      value: 37.11798353023653
    - type: nauc_mrr_at_3_max
      value: -41.98131493735321
    - type: nauc_mrr_at_3_std
      value: -14.708927784488285
    - type: nauc_mrr_at_5_diff1
      value: 36.89165099595256
    - type: nauc_mrr_at_5_max
      value: -46.62294841562043
    - type: nauc_mrr_at_5_std
      value: -12.950360469740291
    - type: nauc_ndcg_at_1000_diff1
      value: 31.229868567293867
    - type: nauc_ndcg_at_1000_max
      value: -32.96979900127197
    - type: nauc_ndcg_at_1000_std
      value: 28.83389826789891
    - type: nauc_ndcg_at_100_diff1
      value: 36.52267538437917
    - type: nauc_ndcg_at_100_max
      value: -36.30568539371575
    - type: nauc_ndcg_at_100_std
      value: 21.077780005544017
    - type: nauc_ndcg_at_10_diff1
      value: 35.624818340564026
    - type: nauc_ndcg_at_10_max
      value: -30.41197929897389
    - type: nauc_ndcg_at_10_std
      value: -2.0879378834665285
    - type: nauc_ndcg_at_1_diff1
      value: 26.09620989819088
    - type: nauc_ndcg_at_1_max
      value: -36.21961356590305
    - type: nauc_ndcg_at_1_std
      value: -16.336654888564233
    - type: nauc_ndcg_at_20_diff1
      value: 33.145204376285356
    - type: nauc_ndcg_at_20_max
      value: -31.28329863036936
    - type: nauc_ndcg_at_20_std
      value: -0.4725530619650745
    - type: nauc_ndcg_at_3_diff1
      value: 26.677773521665433
    - type: nauc_ndcg_at_3_max
      value: -32.429541360857414
    - type: nauc_ndcg_at_3_std
      value: -5.50717933012337
    - type: nauc_ndcg_at_5_diff1
      value: 27.43507358400893
    - type: nauc_ndcg_at_5_max
      value: -31.930933021675834
    - type: nauc_ndcg_at_5_std
      value: -2.223314270488071
    - type: nauc_precision_at_1000_diff1
      value: -27.19395370994479
    - type: nauc_precision_at_1000_max
      value: 31.32895786519588
    - type: nauc_precision_at_1000_std
      value: 30.385879238372826
    - type: nauc_precision_at_100_diff1
      value: 18.037320798123492
    - type: nauc_precision_at_100_max
      value: -12.829019500448858
    - type: nauc_precision_at_100_std
      value: 63.7252345522221
    - type: nauc_precision_at_10_diff1
      value: 33.03740695134771
    - type: nauc_precision_at_10_max
      value: -28.3418055223018
    - type: nauc_precision_at_10_std
      value: 12.399749606566802
    - type: nauc_precision_at_1_diff1
      value: 30.580995175260696
    - type: nauc_precision_at_1_max
      value: -41.150802011358095
    - type: nauc_precision_at_1_std
      value: -18.734158460340613
    - type: nauc_precision_at_20_diff1
      value: 24.61739751282666
    - type: nauc_precision_at_20_max
      value: -26.19505578353661
    - type: nauc_precision_at_20_std
      value: 28.082166318953462
    - type: nauc_precision_at_3_diff1
      value: 24.262619325154343
    - type: nauc_precision_at_3_max
      value: -35.16939673443783
    - type: nauc_precision_at_3_std
      value: -1.5143701562969083
    - type: nauc_precision_at_5_diff1
      value: 22.767486223120752
    - type: nauc_precision_at_5_max
      value: -32.39632845953219
    - type: nauc_precision_at_5_std
      value: 4.989881878186032
    - type: nauc_recall_at_1000_diff1
      value: -3.2461494312684294
    - type: nauc_recall_at_1000_max
      value: -2.112903285457026
    - type: nauc_recall_at_1000_std
      value: 70.89954510826574
    - type: nauc_recall_at_100_diff1
      value: 29.802898837494297
    - type: nauc_recall_at_100_max
      value: -24.20480944377232
    - type: nauc_recall_at_100_std
      value: 35.89183425780783
    - type: nauc_recall_at_10_diff1
      value: 27.388757054959328
    - type: nauc_recall_at_10_max
      value: -24.989779334676186
    - type: nauc_recall_at_10_std
      value: -9.164641938439107
    - type: nauc_recall_at_1_diff1
      value: 38.988840017170084
    - type: nauc_recall_at_1_max
      value: -32.91111385240854
    - type: nauc_recall_at_1_std
      value: -23.593390331872705
    - type: nauc_recall_at_20_diff1
      value: 24.6080131937692
    - type: nauc_recall_at_20_max
      value: -23.05479953156405
    - type: nauc_recall_at_20_std
      value: 0.059402669402089325
    - type: nauc_recall_at_3_diff1
      value: 27.848810363284425
    - type: nauc_recall_at_3_max
      value: -36.53123928519583
    - type: nauc_recall_at_3_std
      value: -19.758588460277824
    - type: nauc_recall_at_5_diff1
      value: 19.64218420357169
    - type: nauc_recall_at_5_max
      value: -29.08402015074908
    - type: nauc_recall_at_5_std
      value: -14.506685298292496
    - type: ndcg_at_1
      value: 38.775999999999996
    - type: ndcg_at_10
      value: 29.148000000000003
    - type: ndcg_at_100
      value: 40.945
    - type: ndcg_at_1000
      value: 52.303999999999995
    - type: ndcg_at_20
      value: 29.848000000000003
    - type: ndcg_at_3
      value: 33.222
    - type: ndcg_at_5
      value: 31.175000000000004
    - type: precision_at_1
      value: 40.816
    - type: precision_at_10
      value: 25.509999999999998
    - type: precision_at_100
      value: 8.347
    - type: precision_at_1000
      value: 1.5939999999999999
    - type: precision_at_20
      value: 19.082
    - type: precision_at_3
      value: 34.694
    - type: precision_at_5
      value: 31.019999999999996
    - type: recall_at_1
      value: 2.9690000000000003
    - type: recall_at_10
      value: 18.979
    - type: recall_at_100
      value: 50.932
    - type: recall_at_1000
      value: 85.402
    - type: recall_at_20
      value: 27.116
    - type: recall_at_3
      value: 7.619
    - type: recall_at_5
      value: 11.448
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 89.27734375
    - type: ap
      value: 35.194960239779064
    - type: ap_weighted
      value: 35.194960239779064
    - type: f1
      value: 74.3697271257718
    - type: f1_weighted
      value: 90.81303890497676
    - type: main_score
      value: 89.27734375
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 76.3469156762875
    - type: f1
      value: 76.53667544013393
    - type: f1_weighted
      value: 75.88734027230643
    - type: main_score
      value: 76.3469156762875
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: main_score
      value: 49.32687063841142
    - type: v_measure
      value: 49.32687063841142
    - type: v_measure_std
      value: 1.4415471512453628
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cosine_accuracy
      value: 85.24169994635513
    - type: cosine_accuracy_threshold
      value: 91.52344465255737
    - type: cosine_ap
      value: 71.43912939014582
    - type: cosine_f1
      value: 66.87586293460525
    - type: cosine_f1_threshold
      value: 90.44243097305298
    - type: cosine_precision
      value: 63.777830979171654
    - type: cosine_recall
      value: 70.29023746701847
    - type: dot_accuracy
      value: 85.24169994635513
    - type: dot_accuracy_threshold
      value: 91.52344465255737
    - type: dot_ap
      value: 71.43910347543935
    - type: dot_f1
      value: 66.87586293460525
    - type: dot_f1_threshold
      value: 90.44243693351746
    - type: dot_precision
      value: 63.777830979171654
    - type: dot_recall
      value: 70.29023746701847
    - type: euclidean_accuracy
      value: 85.24169994635513
    - type: euclidean_accuracy_threshold
      value: 41.17414355278015
    - type: euclidean_ap
      value: 71.43911775197303
    - type: euclidean_f1
      value: 66.87586293460525
    - type: euclidean_f1_threshold
      value: 43.72085928916931
    - type: euclidean_precision
      value: 63.777830979171654
    - type: euclidean_recall
      value: 70.29023746701847
    - type: main_score
      value: 71.43912939014582
    - type: manhattan_accuracy
      value: 85.02115992132086
    - type: manhattan_accuracy_threshold
      value: 970.2783584594727
    - type: manhattan_ap
      value: 71.11811615315935
    - type: manhattan_f1
      value: 66.46334024643161
    - type: manhattan_f1_threshold
      value: 1044.2398071289062
    - type: manhattan_precision
      value: 61.81075561606535
    - type: manhattan_recall
      value: 71.87335092348285
    - type: max_ap
      value: 71.43912939014582
    - type: max_f1
      value: 66.87586293460525
    - type: max_precision
      value: 63.777830979171654
    - type: max_recall
      value: 71.87335092348285
    - type: similarity_accuracy
      value: 85.24169994635513
    - type: similarity_accuracy_threshold
      value: 91.52344465255737
    - type: similarity_ap
      value: 71.43912939014582
    - type: similarity_f1
      value: 66.87586293460525
    - type: similarity_f1_threshold
      value: 90.44243097305298
    - type: similarity_precision
      value: 63.777830979171654
    - type: similarity_recall
      value: 70.29023746701847
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cosine_accuracy
      value: 88.85590095859045
    - type: cosine_accuracy_threshold
      value: 88.8430118560791
    - type: cosine_ap
      value: 85.68756441554032
    - type: cosine_f1
      value: 77.73691444704485
    - type: cosine_f1_threshold
      value: 87.81020641326904
    - type: cosine_precision
      value: 75.10587897494796
    - type: cosine_recall
      value: 80.55897751770866
    - type: dot_accuracy
      value: 88.85590095859045
    - type: dot_accuracy_threshold
      value: 88.84301781654358
    - type: dot_ap
      value: 85.6875209900991
    - type: dot_f1
      value: 77.73691444704485
    - type: dot_f1_threshold
      value: 87.810218334198
    - type: dot_precision
      value: 75.10587897494796
    - type: dot_recall
      value: 80.55897751770866
    - type: euclidean_accuracy
      value: 88.85590095859045
    - type: euclidean_accuracy_threshold
      value: 47.23767042160034
    - type: euclidean_ap
      value: 85.68752572543856
    - type: euclidean_f1
      value: 77.73691444704485
    - type: euclidean_f1_threshold
      value: 49.375683069229126
    - type: euclidean_precision
      value: 75.10587897494796
    - type: euclidean_recall
      value: 80.55897751770866
    - type: main_score
      value: 85.68756441554032
    - type: manhattan_accuracy
      value: 88.86366282454303
    - type: manhattan_accuracy_threshold
      value: 1111.7809295654297
    - type: manhattan_ap
      value: 85.65387985046206
    - type: manhattan_f1
      value: 77.74802915365164
    - type: manhattan_f1_threshold
      value: 1163.0821228027344
    - type: manhattan_precision
      value: 75.18699654775605
    - type: manhattan_recall
      value: 80.48968278410841
    - type: max_ap
      value: 85.68756441554032
    - type: max_f1
      value: 77.74802915365164
    - type: max_precision
      value: 75.18699654775605
    - type: max_recall
      value: 80.55897751770866
    - type: similarity_accuracy
      value: 88.85590095859045
    - type: similarity_accuracy_threshold
      value: 88.8430118560791
    - type: similarity_ap
      value: 85.68756441554032
    - type: similarity_f1
      value: 77.73691444704485
    - type: similarity_f1_threshold
      value: 87.81020641326904
    - type: similarity_precision
      value: 75.10587897494796
    - type: similarity_recall
      value: 80.55897751770866
  - task:
      type: STS
    dataset:
      name: MTEB AFQMC
      type: C-MTEB/AFQMC
      config: default
      split: validation
      revision: b44c3b011063adb25877c13823db83bb193913c4
    metrics:
    - type: cosine_pearson
      value: 37.12876239452581
    - type: cosine_spearman
      value: 38.067257174211036
    - type: euclidean_pearson
      value: 36.735658383168044
    - type: euclidean_spearman
      value: 38.06725717137013
    - type: main_score
      value: 38.067257174211036
    - type: manhattan_pearson
      value: 36.43829602976309
    - type: manhattan_spearman
      value: 37.73959740816105
    - type: pearson
      value: 37.12876239452581
    - type: spearman
      value: 38.067257174211036
  - task:
      type: STS
    dataset:
      name: MTEB ATEC
      type: C-MTEB/ATEC
      config: default
      split: test
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
    metrics:
    - type: cosine_pearson
      value: 45.55151167790002
    - type: cosine_spearman
      value: 46.22151486832593
    - type: euclidean_pearson
      value: 48.31921364975583
    - type: euclidean_spearman
      value: 46.22151824485588
    - type: main_score
      value: 46.22151486832593
    - type: manhattan_pearson
      value: 48.12062382773407
    - type: manhattan_spearman
      value: 46.00780031287469
    - type: pearson
      value: 45.55151167790002
    - type: spearman
      value: 46.22151486832593
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 50.978
    - type: f1
      value: 47.04754599162115
    - type: f1_weighted
      value: 47.04754599162114
    - type: main_score
      value: 50.978
  - task:
      type: STS
    dataset:
      name: MTEB BQ
      type: C-MTEB/BQ
      config: default
      split: test
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
    metrics:
    - type: cosine_pearson
      value: 53.84488943094217
    - type: cosine_spearman
      value: 54.49605523234321
    - type: euclidean_pearson
      value: 53.50943690170382
    - type: euclidean_spearman
      value: 54.49605869546392
    - type: main_score
      value: 54.49605523234321
    - type: manhattan_pearson
      value: 53.24052011197216
    - type: manhattan_spearman
      value: 54.215799016988996
    - type: pearson
      value: 53.84488943094217
    - type: spearman
      value: 54.49605523234321
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringP2P
      type: C-MTEB/CLSClusteringP2P
      config: default
      split: test
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
    metrics:
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      value: 46.915444917880286
    - type: v_measure
      value: 46.915444917880286
    - type: v_measure_std
      value: 1.5837973591025165
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringS2S
      type: C-MTEB/CLSClusteringS2S
      config: default
      split: test
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
    metrics:
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      value: 44.89461372862163
    - type: v_measure
      value: 44.89461372862163
    - type: v_measure_std
      value: 1.0128909727353739
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv1
      type: C-MTEB/CMedQAv1-reranking
      config: default
      split: test
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
    metrics:
    - type: main_score
      value: 82.21191216422777
    - type: map
      value: 82.21191216422777
    - type: mrr
      value: 84.98567460317462
    - type: nAUC_map_diff1
      value: 55.27793122843884
    - type: nAUC_map_max
      value: 61.78021845841622
    - type: nAUC_map_std
      value: 24.32874017213633
    - type: nAUC_mrr_diff1
      value: 62.56855683834338
    - type: nAUC_mrr_max
      value: 69.83242448232605
    - type: nAUC_mrr_std
      value: 30.753945346898497
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv2
      type: C-MTEB/CMedQAv2-reranking
      config: default
      split: test
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
    metrics:
    - type: main_score
      value: 83.08227189741763
    - type: map
      value: 83.08227189741763
    - type: mrr
      value: 86.19051587301587
    - type: nAUC_map_diff1
      value: 58.735936259553654
    - type: nAUC_map_max
      value: 60.14841462146858
    - type: nAUC_map_std
      value: 17.761882943403222
    - type: nAUC_mrr_diff1
      value: 67.43320028439246
    - type: nAUC_mrr_max
      value: 70.96971853942028
    - type: nAUC_mrr_std
      value: 27.963212156051533
  - task:
      type: Retrieval
    dataset:
      name: MTEB CmedqaRetrieval
      type: C-MTEB/CmedqaRetrieval
      config: default
      split: dev
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
    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
      value: 36.855
    - type: map_at_3
      value: 32.263
    - type: map_at_5
      value: 34.458
    - 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: nauc_recall_at_5_diff1
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      value: 29.81974055210633
    - type: nauc_recall_at_5_std
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    - type: ndcg_at_1
      value: 37.809
    - type: ndcg_at_10
      value: 42.114000000000004
    - type: ndcg_at_100
      value: 48.76
    - type: ndcg_at_1000
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    - type: ndcg_at_20
      value: 44.528
    - type: ndcg_at_3
      value: 37.621
    - type: ndcg_at_5
      value: 39.627
    - type: precision_at_1
      value: 37.809
    - type: precision_at_10
      value: 9.215
    - type: precision_at_100
      value: 1.468
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_20
      value: 5.423
    - type: precision_at_3
      value: 21.214
    - type: precision_at_5
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    - type: recall_at_1
      value: 24.712999999999997
    - type: recall_at_10
      value: 51.08200000000001
    - type: recall_at_100
      value: 78.855
    - type: recall_at_1000
      value: 96.897
    - type: recall_at_20
      value: 59.232
    - type: recall_at_3
      value: 37.147000000000006
    - type: recall_at_5
      value: 43.579
  - task:
      type: PairClassification
    dataset:
      name: MTEB Cmnli
      type: C-MTEB/CMNLI
      config: default
      split: validation
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
    metrics:
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      value: 69.70535177390259
    - type: cosine_accuracy_threshold
      value: 85.75683832168579
    - type: cosine_ap
      value: 76.66113306358733
    - type: cosine_f1
      value: 72.686230248307
    - type: cosine_f1_threshold
      value: 82.12493658065796
    - type: cosine_precision
      value: 62.63531799729364
    - type: cosine_recall
      value: 86.57937806873977
    - type: dot_accuracy
      value: 69.70535177390259
    - type: dot_accuracy_threshold
      value: 85.75684428215027
    - type: dot_ap
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    - type: dot_f1
      value: 72.686230248307
    - type: dot_f1_threshold
      value: 82.12493658065796
    - type: dot_precision
      value: 62.63531799729364
    - type: dot_recall
      value: 86.57937806873977
    - type: euclidean_accuracy
      value: 69.70535177390259
    - type: euclidean_accuracy_threshold
      value: 53.37257385253906
    - type: euclidean_ap
      value: 76.6611302634097
    - type: euclidean_f1
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    - type: euclidean_f1_threshold
      value: 59.79139804840088
    - 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_accuracy_threshold
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    - type: manhattan_ap
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    - type: manhattan_f1
      value: 72.39749155812832
    - 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
      value: 72.686230248307
    - type: max_precision
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    - type: max_recall
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    - type: similarity_accuracy
      value: 69.70535177390259
    - 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
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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: mrr_at_100
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    - type: mrr_at_1000
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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: 35.4035877894852
    - type: f1_weighted
      value: 45.154890336987165
    - type: main_score
      value: 48.54944209311274
  - task:
      type: Classification
    dataset:
      name: MTEB JDReview
      type: C-MTEB/JDReview-classification
      config: default
      split: test
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
    metrics:
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    - type: ap
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    - type: ap_weighted
      value: 50.14519497969601
    - type: f1
      value: 77.87333673269332
    - type: f1_weighted
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    - type: main_score
      value: 83.11444652908067
  - task:
      type: STS
    dataset:
      name: MTEB LCQMC
      type: C-MTEB/LCQMC
      config: default
      split: test
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
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    - type: euclidean_pearson
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    - type: euclidean_spearman
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    - type: main_score
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    - type: manhattan_pearson
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    - type: manhattan_spearman
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    - type: pearson
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    - type: spearman
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  - task:
      type: Reranking
    dataset:
      name: MTEB MMarcoReranking
      type: C-MTEB/Mmarco-reranking
      config: default
      split: dev
      revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
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  - task:
      type: Retrieval
    dataset:
      name: MTEB MMarcoRetrieval
      type: C-MTEB/MMarcoRetrieval
      config: default
      split: dev
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
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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
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  - 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: 68.52723604572965
    - type: f1
      value: 65.11440259918176
    - type: f1_weighted
      value: 67.36553063592758
    - type: main_score
      value: 68.52723604572965
  - 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: 60.00672494956289
    - type: f1
      value: 57.630108926504654
    - type: f1_weighted
      value: 58.013112273357294
    - type: main_score
      value: 60.00672494956289
  - 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: 75.48755884330868
    - type: f1
      value: 74.96341150854326
    - type: f1_weighted
      value: 75.11344709750414
    - type: main_score
      value: 75.48755884330868
  - 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: 69.20645595158035
    - type: f1
      value: 69.57805291990489
    - type: f1_weighted
      value: 68.41325928547694
    - type: main_score
      value: 69.20645595158035
  - task:
      type: Retrieval
    dataset:
      name: MTEB MedicalRetrieval
      type: C-MTEB/MedicalRetrieval
      config: default
      split: dev
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
    metrics:
    - type: main_score
      value: 56.842999999999996
    - type: map_at_1
      value: 48.4
    - type: map_at_10
      value: 54.127
    - 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
      value: 48.4
    - type: mrr_at_10
      value: 54.12742063492064
    - type: mrr_at_100
      value: 54.74007856972957
    - 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: mrr_at_5
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    - type: nauc_map_at_1000_diff1
      value: 78.4025670906739
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    - type: nauc_recall_at_1000_diff1
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    - type: nauc_recall_at_5_diff1
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    - type: nauc_recall_at_5_max
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    - type: nauc_recall_at_5_std
      value: 25.61766349916154
    - type: ndcg_at_1
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    - type: ndcg_at_10
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    - type: ndcg_at_100
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    - type: ndcg_at_1000
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    - type: ndcg_at_20
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    - type: ndcg_at_3
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    - type: ndcg_at_5
      value: 55.435
    - type: precision_at_1
      value: 48.4
    - type: precision_at_10
      value: 6.54
    - type: precision_at_100
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    - type: precision_at_1000
      value: 0.094
    - type: precision_at_20
      value: 3.54
    - type: precision_at_3
      value: 19.400000000000002
    - type: precision_at_5
      value: 12.2
    - type: recall_at_1
      value: 48.4
    - type: recall_at_10
      value: 65.4
    - type: recall_at_100
      value: 80.9
    - type: recall_at_1000
      value: 93.60000000000001
    - type: recall_at_20
      value: 70.8
    - type: recall_at_3
      value: 58.199999999999996
    - type: recall_at_5
      value: 61.0
  - task:
      type: Classification
    dataset:
      name: MTEB MultilingualSentiment
      type: C-MTEB/MultilingualSentiment-classification
      config: default
      split: test
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
    metrics:
    - type: accuracy
      value: 78.22
    - type: f1
      value: 77.72387105131016
    - type: f1_weighted
      value: 77.72387105131016
    - type: main_score
      value: 78.22
  - task:
      type: PairClassification
    dataset:
      name: MTEB Ocnli
      type: C-MTEB/OCNLI
      config: default
      split: validation
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
    metrics:
    - type: cosine_accuracy
      value: 66.21548456957228
    - type: cosine_accuracy_threshold
      value: 85.5343759059906
    - type: cosine_ap
      value: 69.21438509764522
    - type: cosine_f1
      value: 70.44534412955467
    - type: cosine_f1_threshold
      value: 83.85478258132935
    - type: cosine_precision
      value: 61.36363636363637
    - type: cosine_recall
      value: 82.68215417106653
    - type: dot_accuracy
      value: 66.21548456957228
    - type: dot_accuracy_threshold
      value: 85.5343759059906
    - type: dot_ap
      value: 69.21438509764522
    - type: dot_f1
      value: 70.44534412955467
    - type: dot_f1_threshold
      value: 83.85477662086487
    - type: dot_precision
      value: 61.36363636363637
    - type: dot_recall
      value: 82.68215417106653
    - type: euclidean_accuracy
      value: 66.21548456957228
    - type: euclidean_accuracy_threshold
      value: 53.787779808044434
    - type: euclidean_ap
      value: 69.21438509764522
    - type: euclidean_f1
      value: 70.44534412955467
    - type: euclidean_f1_threshold
      value: 56.82467818260193
    - type: euclidean_precision
      value: 61.36363636363637
    - type: euclidean_recall
      value: 82.68215417106653
    - type: main_score
      value: 69.21438509764522
    - type: manhattan_accuracy
      value: 65.89063345966431
    - type: manhattan_accuracy_threshold
      value: 1257.1067810058594
    - type: manhattan_ap
      value: 68.93169452602294
    - type: manhattan_f1
      value: 70.018281535649
    - type: manhattan_f1_threshold
      value: 1321.6852188110352
    - type: manhattan_precision
      value: 61.72441579371475
    - type: manhattan_recall
      value: 80.8870116156283
    - type: max_ap
      value: 69.21438509764522
    - type: max_f1
      value: 70.44534412955467
    - type: max_precision
      value: 61.72441579371475
    - type: max_recall
      value: 82.68215417106653
    - type: similarity_accuracy
      value: 66.21548456957228
    - type: similarity_accuracy_threshold
      value: 85.5343759059906
    - type: similarity_ap
      value: 69.21438509764522
    - type: similarity_f1
      value: 70.44534412955467
    - type: similarity_f1_threshold
      value: 83.85478258132935
    - type: similarity_precision
      value: 61.36363636363637
    - type: similarity_recall
      value: 82.68215417106653
  - task:
      type: Classification
    dataset:
      name: MTEB OnlineShopping
      type: C-MTEB/OnlineShopping-classification
      config: default
      split: test
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
    metrics:
    - type: accuracy
      value: 93.09
    - type: ap
      value: 92.02754366798146
    - type: ap_weighted
      value: 92.02754366798146
    - type: f1
      value: 93.08751542879655
    - type: f1_weighted
      value: 93.092429173112
    - type: main_score
      value: 93.09
  - task:
      type: STS
    dataset:
      name: MTEB PAWSX
      type: C-MTEB/PAWSX
      config: default
      split: test
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
    metrics:
    - type: cosine_pearson
      value: 14.700393205389778
    - type: cosine_spearman
      value: 16.3328315656736
    - type: euclidean_pearson
      value: 18.37941425496121
    - type: euclidean_spearman
      value: 16.35419723095118
    - type: main_score
      value: 16.3328315656736
    - type: manhattan_pearson
      value: 18.461692452314196
    - type: manhattan_spearman
      value: 16.49877203419426
    - type: pearson
      value: 14.700393205389778
    - type: spearman
      value: 16.3328315656736
  - task:
      type: STS
    dataset:
      name: MTEB QBQTC
      type: C-MTEB/QBQTC
      config: default
      split: test
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
    metrics:
    - type: cosine_pearson
      value: 31.771341848950048
    - type: cosine_spearman
      value: 35.21248641540282
    - type: euclidean_pearson
      value: 32.86721005963099
    - type: euclidean_spearman
      value: 35.21281584988107
    - type: main_score
      value: 35.21248641540282
    - type: manhattan_pearson
      value: 32.994593737560464
    - type: manhattan_spearman
      value: 35.29332061037625
    - type: pearson
      value: 31.771341848950048
    - type: spearman
      value: 35.21248641540282
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 74.05009462610907
    - type: cosine_spearman
      value: 73.57662463047618
    - type: euclidean_pearson
      value: 71.97192342862905
    - type: euclidean_spearman
      value: 73.57662463047618
    - type: main_score
      value: 73.57662463047618
    - type: manhattan_pearson
      value: 71.66171363912555
    - type: manhattan_spearman
      value: 73.33995365752388
    - type: pearson
      value: 74.05009462610907
    - type: spearman
      value: 73.57662463047618
  - task:
      type: STS
    dataset:
      name: MTEB STSB
      type: C-MTEB/STSB
      config: default
      split: test
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
    metrics:
    - type: cosine_pearson
      value: 76.44164798054604
    - type: cosine_spearman
      value: 77.80818016295537
    - type: euclidean_pearson
      value: 77.23235480541429
    - type: euclidean_spearman
      value: 77.80820115269609
    - type: main_score
      value: 77.80818016295537
    - type: manhattan_pearson
      value: 77.1383518573764
    - type: manhattan_spearman
      value: 77.74335331319868
    - type: pearson
      value: 76.44164798054604
    - type: spearman
      value: 77.80818016295537
  - task:
      type: Reranking
    dataset:
      name: MTEB T2Reranking
      type: C-MTEB/T2Reranking
      config: default
      split: dev
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
    metrics:
    - type: main_score
      value: 66.73229864475817
    - type: map
      value: 66.73229864475817
    - type: mrr
      value: 76.93718364122901
    - type: nAUC_map_diff1
      value: -10.073077377159336
    - type: nAUC_map_max
      value: 36.06382407917089
    - type: nAUC_map_std
      value: -2.3465936800383975
    - type: nAUC_mrr_diff1
      value: -7.614514359731517
    - type: nAUC_mrr_max
      value: 29.970126517689895
    - type: nAUC_mrr_std
      value: -4.000393719743965
  - task:
      type: Retrieval
    dataset:
      name: MTEB T2Retrieval
      type: C-MTEB/T2Retrieval
      config: default
      split: dev
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
    metrics:
    - type: main_score
      value: 84.066
    - type: map_at_1
      value: 27.311999999999998
    - type: map_at_10
      value: 76.45100000000001
    - type: map_at_100
      value: 80.081
    - type: map_at_1000
      value: 80.148
    - type: map_at_20
      value: 79.19500000000001
    - type: map_at_3
      value: 53.785000000000004
    - type: map_at_5
      value: 66.08800000000001
    - type: mrr_at_1
      value: 89.5493599859723
    - type: mrr_at_10
      value: 92.04882420558401
    - type: mrr_at_100
      value: 92.13851397485055
    - type: mrr_at_1000
      value: 92.142380377799
    - type: mrr_at_20
      value: 92.10835206390658
    - type: mrr_at_3
      value: 91.55634461394584
    - type: mrr_at_5
      value: 91.86626921503318
    - type: nauc_map_at_1000_diff1
      value: 13.881593411464955
    - type: nauc_map_at_1000_max
      value: 45.98958134604669
    - type: nauc_map_at_1000_std
      value: 20.749937417202162
    - type: nauc_map_at_100_diff1
      value: 13.897201544868256
    - type: nauc_map_at_100_max
      value: 45.8975771537659
    - type: nauc_map_at_100_std
      value: 20.702471991537816
    - type: nauc_map_at_10_diff1
      value: 18.574187481021404
    - type: nauc_map_at_10_max
      value: 33.03798476409084
    - type: nauc_map_at_10_std
      value: 4.923864341255681
    - type: nauc_map_at_1_diff1
      value: 53.60647320762889
    - type: nauc_map_at_1_max
      value: -25.482104681284262
    - type: nauc_map_at_1_std
      value: -35.242254755025314
    - type: nauc_map_at_20_diff1
      value: 14.659565827642442
    - type: nauc_map_at_20_max
      value: 43.28938016609046
    - type: nauc_map_at_20_std
      value: 17.356608121513382
    - type: nauc_map_at_3_diff1
      value: 39.4070801457046
    - type: nauc_map_at_3_max
      value: -12.578348941863455
    - type: nauc_map_at_3_std
      value: -31.8798104413808
    - type: nauc_map_at_5_diff1
      value: 31.32071840697937
    - type: nauc_map_at_5_max
      value: 4.002877899741811
    - type: nauc_map_at_5_std
      value: -21.303079028844135
    - type: nauc_mrr_at_1000_diff1
      value: 46.83368353209455
    - type: nauc_mrr_at_1000_max
      value: 75.71133032423971
    - type: nauc_mrr_at_1000_std
      value: 39.48046724592415
    - type: nauc_mrr_at_100_diff1
      value: 46.83586223804469
    - type: nauc_mrr_at_100_max
      value: 75.72076556031453
    - type: nauc_mrr_at_100_std
      value: 39.499587346326805
    - type: nauc_mrr_at_10_diff1
      value: 46.844356562367416
    - type: nauc_mrr_at_10_max
      value: 75.82630788248727
    - type: nauc_mrr_at_10_std
      value: 39.57574348115377
    - type: nauc_mrr_at_1_diff1
      value: 47.31173835991697
    - type: nauc_mrr_at_1_max
      value: 71.62100768371566
    - type: nauc_mrr_at_1_std
      value: 33.215001055441654
    - type: nauc_mrr_at_20_diff1
      value: 46.81803840032271
    - type: nauc_mrr_at_20_max
      value: 75.77378447923428
    - type: nauc_mrr_at_20_std
      value: 39.56872022078684
    - type: nauc_mrr_at_3_diff1
      value: 46.860529286384946
    - type: nauc_mrr_at_3_max
      value: 75.76461859710832
    - type: nauc_mrr_at_3_std
      value: 39.2216938919496
    - type: nauc_mrr_at_5_diff1
      value: 46.789493616730475
    - type: nauc_mrr_at_5_max
      value: 75.90313095614088
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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
    metrics:
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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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  - task:
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    dataset:
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      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:
      type: Clustering
    dataset:
      name: MTEB AlloProfClusteringP2P
      type: lyon-nlp/alloprof
      config: default
      split: test
      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
    metrics:
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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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      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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  - task:
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      type: maastrichtlawtech/bsard
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  - task:
      type: Clustering
    dataset:
      name: MTEB HALClusteringS2S
      type: lyon-nlp/clustering-hal-s2s
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      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:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (fr)
      type: mteb/mtop_domain
      config: fr
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 95.01722518008143
    - type: f1
      value: 94.84287480029258
    - type: f1_weighted
      value: 95.0452443472173
    - type: main_score
      value: 95.01722518008143
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (fr)
      type: mteb/mtop_intent
      config: fr
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 79.74945192608833
    - type: f1
      value: 53.733289773568536
    - type: f1_weighted
      value: 79.64257473311346
    - type: main_score
      value: 79.74945192608833
  - task:
      type: Classification
    dataset:
      name: MTEB MasakhaNEWSClassification (fra)
      type: mteb/masakhanews
      config: fra
      split: test
      revision: 18193f187b92da67168c655c9973a165ed9593dd
    metrics:
    - type: accuracy
      value: 83.3649289099526
    - type: f1
      value: 79.77180137779536
    - type: f1_weighted
      value: 83.01264683214308
    - type: main_score
      value: 83.3649289099526
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (fra)
      type: masakhane/masakhanews
      config: fra
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 56.59401317251221
    - type: v_measure
      value: 56.59401317251221
    - type: v_measure_std
      value: 36.0760983348482
    - type: main_score
      value: 71.82457224763512
    - type: v_measure
      value: 71.82457224763512
    - type: v_measure_std
      value: 33.00235264955351
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fr)
      type: mteb/amazon_massive_intent
      config: fr
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 66.61398789509077
    - type: f1
      value: 60.956092562089324
    - type: f1_weighted
      value: 64.68321586762302
    - type: main_score
      value: 66.61398789509077
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (fr)
      type: mteb/amazon_massive_scenario
      config: fr
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 75.68594485541358
    - type: f1
      value: 74.71713629733614
    - type: f1_weighted
      value: 75.49907502505853
    - type: main_score
      value: 75.68594485541358
  - task:
      type: Retrieval
    dataset:
      name: MTEB MintakaRetrieval (fr)
      type: jinaai/mintakaqa
      config: fr
      split: test
      revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
    metrics:
    - type: main_score
      value: 28.939999999999998
    - type: map_at_1
      value: 16.585
    - type: map_at_10
      value: 24.496000000000002
    - type: map_at_100
      value: 25.769
    - type: map_at_1000
      value: 25.857999999999997
    - type: map_at_20
      value: 25.224000000000004
    - type: map_at_3
      value: 21.908
    - type: map_at_5
      value: 23.464
    - type: mrr_at_1
      value: 16.584766584766587
    - type: mrr_at_10
      value: 24.49603824603824
    - type: mrr_at_100
      value: 25.76910538724444
    - type: mrr_at_1000
      value: 25.857970951595167
    - type: mrr_at_20
      value: 25.223803880220952
    - type: mrr_at_3
      value: 21.908271908271885
    - type: mrr_at_5
      value: 23.46437346437344
    - type: nauc_map_at_1000_diff1
      value: 24.449324509741782
    - type: nauc_map_at_1000_max
      value: 16.857551392045668
    - type: nauc_map_at_1000_std
      value: 9.029392522714542
    - type: nauc_map_at_100_diff1
      value: 24.416377398368994
    - type: nauc_map_at_100_max
      value: 16.874285303124278
    - type: nauc_map_at_100_std
      value: 9.042769202417494
    - type: nauc_map_at_10_diff1
      value: 24.30792102146879
    - type: nauc_map_at_10_max
      value: 16.618278881262178
    - type: nauc_map_at_10_std
      value: 8.925464095934705
    - type: nauc_map_at_1_diff1
      value: 29.76904844307235
    - type: nauc_map_at_1_max
      value: 14.721060890557535
    - type: nauc_map_at_1_std
      value: 4.1356111912072935
    - type: nauc_map_at_20_diff1
      value: 24.42346651590614
    - type: nauc_map_at_20_max
      value: 16.780464496035194
    - type: nauc_map_at_20_std
      value: 8.981541510161698
    - type: nauc_map_at_3_diff1
      value: 25.463420671464554
    - type: nauc_map_at_3_max
      value: 16.4183897697643
    - type: nauc_map_at_3_std
      value: 7.625690829397712
    - type: nauc_map_at_5_diff1
      value: 24.93868444905917
    - type: nauc_map_at_5_max
      value: 16.091635346098528
    - type: nauc_map_at_5_std
      value: 8.39683861182176
    - type: nauc_mrr_at_1000_diff1
      value: 24.449324509741782
    - type: nauc_mrr_at_1000_max
      value: 16.857551392045668
    - type: nauc_mrr_at_1000_std
      value: 9.029392522714542
    - type: nauc_mrr_at_100_diff1
      value: 24.416377398368994
    - type: nauc_mrr_at_100_max
      value: 16.874285303124278
    - type: nauc_mrr_at_100_std
      value: 9.042769202417494
    - type: nauc_mrr_at_10_diff1
      value: 24.30792102146879
    - type: nauc_mrr_at_10_max
      value: 16.618278881262178
    - type: nauc_mrr_at_10_std
      value: 8.925464095934705
    - type: nauc_mrr_at_1_diff1
      value: 29.76904844307235
    - type: nauc_mrr_at_1_max
      value: 14.721060890557535
    - type: nauc_mrr_at_1_std
      value: 4.1356111912072935
    - type: nauc_mrr_at_20_diff1
      value: 24.42346651590614
    - type: nauc_mrr_at_20_max
      value: 16.780464496035194
    - type: nauc_mrr_at_20_std
      value: 8.981541510161698
    - type: nauc_mrr_at_3_diff1
      value: 25.463420671464554
    - type: nauc_mrr_at_3_max
      value: 16.4183897697643
    - type: nauc_mrr_at_3_std
      value: 7.625690829397712
    - type: nauc_mrr_at_5_diff1
      value: 24.93868444905917
    - type: nauc_mrr_at_5_max
      value: 16.091635346098528
    - type: nauc_mrr_at_5_std
      value: 8.39683861182176
    - type: nauc_ndcg_at_1000_diff1
      value: 23.235835294659104
    - type: nauc_ndcg_at_1000_max
      value: 18.130069784749416
    - type: nauc_ndcg_at_1000_std
      value: 11.373761760081479
    - type: nauc_ndcg_at_100_diff1
      value: 22.573685299807515
    - type: nauc_ndcg_at_100_max
      value: 18.932477112977686
    - type: nauc_ndcg_at_100_std
      value: 12.149429764085687
    - type: nauc_ndcg_at_10_diff1
      value: 22.056289907300375
    - type: nauc_ndcg_at_10_max
      value: 17.44090382465399
    - type: nauc_ndcg_at_10_std
      value: 11.078636741064129
    - type: nauc_ndcg_at_1_diff1
      value: 29.76904844307235
    - type: nauc_ndcg_at_1_max
      value: 14.721060890557535
    - type: nauc_ndcg_at_1_std
      value: 4.1356111912072935
    - type: nauc_ndcg_at_20_diff1
      value: 22.35349136882196
    - type: nauc_ndcg_at_20_max
      value: 18.085452594784922
    - type: nauc_ndcg_at_20_std
      value: 11.380430365055334
    - type: nauc_ndcg_at_3_diff1
      value: 24.25988476966241
    - type: nauc_ndcg_at_3_max
      value: 16.80378720501912
    - type: nauc_ndcg_at_3_std
      value: 8.666118913493746
    - type: nauc_ndcg_at_5_diff1
      value: 23.43312793787156
    - type: nauc_ndcg_at_5_max
      value: 16.291356652340085
    - type: nauc_ndcg_at_5_std
      value: 9.985808307664348
    - type: nauc_precision_at_1000_diff1
      value: 20.59167291436066
    - type: nauc_precision_at_1000_max
      value: 37.11669863650303
    - type: nauc_precision_at_1000_std
      value: 53.79402863337551
    - type: nauc_precision_at_100_diff1
      value: 16.48046435474148
    - type: nauc_precision_at_100_max
      value: 30.49436900744379
    - type: nauc_precision_at_100_std
      value: 27.593241126791774
    - type: nauc_precision_at_10_diff1
      value: 16.21264848839721
    - type: nauc_precision_at_10_max
      value: 19.68782276242417
    - type: nauc_precision_at_10_std
      value: 16.66213297771153
    - type: nauc_precision_at_1_diff1
      value: 29.76904844307235
    - type: nauc_precision_at_1_max
      value: 14.721060890557535
    - type: nauc_precision_at_1_std
      value: 4.1356111912072935
    - type: nauc_precision_at_20_diff1
      value: 16.782602338251536
    - type: nauc_precision_at_20_max
      value: 22.266838160036038
    - type: nauc_precision_at_20_std
      value: 18.225681654722052
    - type: nauc_precision_at_3_diff1
      value: 21.258021189556455
    - type: nauc_precision_at_3_max
      value: 17.741568150869735
    - type: nauc_precision_at_3_std
      value: 11.278258942650373
    - type: nauc_precision_at_5_diff1
      value: 19.74165284616189
    - type: nauc_precision_at_5_max
      value: 16.72366359140884
    - type: nauc_precision_at_5_std
      value: 13.991493395533237
    - type: nauc_recall_at_1000_diff1
      value: 20.591672914360146
    - type: nauc_recall_at_1000_max
      value: 37.11669863650274
    - type: nauc_recall_at_1000_std
      value: 53.79402863337549
    - type: nauc_recall_at_100_diff1
      value: 16.480464354741507
    - type: nauc_recall_at_100_max
      value: 30.494369007443765
    - type: nauc_recall_at_100_std
      value: 27.59324112679175
    - type: nauc_recall_at_10_diff1
      value: 16.2126484883972
    - type: nauc_recall_at_10_max
      value: 19.6878227624242
    - type: nauc_recall_at_10_std
      value: 16.66213297771157
    - type: nauc_recall_at_1_diff1
      value: 29.76904844307235
    - type: nauc_recall_at_1_max
      value: 14.721060890557535
    - type: nauc_recall_at_1_std
      value: 4.1356111912072935
    - type: nauc_recall_at_20_diff1
      value: 16.782602338251547
    - type: nauc_recall_at_20_max
      value: 22.266838160036027
    - type: nauc_recall_at_20_std
      value: 18.22568165472206
    - type: nauc_recall_at_3_diff1
      value: 21.258021189556477
    - type: nauc_recall_at_3_max
      value: 17.741568150869757
    - type: nauc_recall_at_3_std
      value: 11.278258942650384
    - type: nauc_recall_at_5_diff1
      value: 19.741652846161877
    - type: nauc_recall_at_5_max
      value: 16.723663591408847
    - type: nauc_recall_at_5_std
      value: 13.991493395533256
    - type: ndcg_at_1
      value: 16.585
    - type: ndcg_at_10
      value: 28.939999999999998
    - type: ndcg_at_100
      value: 35.568
    - type: ndcg_at_1000
      value: 38.201
    - type: ndcg_at_20
      value: 31.576999999999998
    - type: ndcg_at_3
      value: 23.634
    - type: ndcg_at_5
      value: 26.462000000000003
    - type: precision_at_1
      value: 16.585
    - type: precision_at_10
      value: 4.316
    - type: precision_at_100
      value: 0.752
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_20
      value: 2.6780000000000004
    - type: precision_at_3
      value: 9.541
    - type: precision_at_5
      value: 7.109
    - type: recall_at_1
      value: 16.585
    - type: recall_at_10
      value: 43.161
    - type: recall_at_100
      value: 75.184
    - type: recall_at_1000
      value: 96.478
    - type: recall_at_20
      value: 53.563
    - type: recall_at_3
      value: 28.624
    - type: recall_at_5
      value: 35.545
  - task:
      type: PairClassification
    dataset:
      name: MTEB OpusparcusPC (fr)
      type: GEM/opusparcus
      config: fr
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    metrics:
    - type: cosine_accuracy
      value: 82.90190735694823
    - type: cosine_accuracy_threshold
      value: 86.7036521434784
    - type: cosine_ap
      value: 93.15630587159856
    - type: cosine_f1
      value: 88.28744750349978
    - type: cosine_f1_threshold
      value: 86.63686513900757
    - type: cosine_precision
      value: 83.27464788732394
    - type: cosine_recall
      value: 93.94240317775571
    - type: dot_accuracy
      value: 82.90190735694823
    - type: dot_accuracy_threshold
      value: 86.70365810394287
    - type: dot_ap
      value: 93.15630587159856
    - type: dot_f1
      value: 88.28744750349978
    - type: dot_f1_threshold
      value: 86.63686513900757
    - type: dot_precision
      value: 83.27464788732394
    - type: dot_recall
      value: 93.94240317775571
    - type: euclidean_accuracy
      value: 82.90190735694823
    - type: euclidean_accuracy_threshold
      value: 51.56809687614441
    - type: euclidean_ap
      value: 93.15630587159856
    - type: euclidean_f1
      value: 88.28744750349978
    - type: euclidean_f1_threshold
      value: 51.69745683670044
    - type: euclidean_precision
      value: 83.27464788732394
    - type: euclidean_recall
      value: 93.94240317775571
    - type: main_score
      value: 93.15630587159856
    - type: manhattan_accuracy
      value: 82.83378746594006
    - type: manhattan_accuracy_threshold
      value: 1203.4871101379395
    - type: manhattan_ap
      value: 93.13986431895378
    - type: manhattan_f1
      value: 88.20224719101122
    - type: manhattan_f1_threshold
      value: 1204.0313720703125
    - type: manhattan_precision
      value: 83.43666961913198
    - type: manhattan_recall
      value: 93.545183714002
    - type: max_ap
      value: 93.15630587159856
    - type: max_f1
      value: 88.28744750349978
    - type: max_precision
      value: 83.43666961913198
    - type: max_recall
      value: 93.94240317775571
    - type: similarity_accuracy
      value: 82.90190735694823
    - type: similarity_accuracy_threshold
      value: 86.7036521434784
    - type: similarity_ap
      value: 93.15630587159856
    - type: similarity_f1
      value: 88.28744750349978
    - type: similarity_f1_threshold
      value: 86.63686513900757
    - type: similarity_precision
      value: 83.27464788732394
    - 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: 61.0
    - type: cosine_accuracy_threshold
      value: 99.4693398475647
    - type: cosine_ap
      value: 60.596634996072794
    - type: cosine_f1
      value: 62.77477477477477
    - type: cosine_f1_threshold
      value: 95.54682970046997
    - type: cosine_precision
      value: 46.52777777777778
    - type: cosine_recall
      value: 96.4562569213732
    - type: dot_accuracy
      value: 61.0
    - type: dot_accuracy_threshold
      value: 99.4693398475647
    - type: dot_ap
      value: 60.60423446409202
    - type: dot_f1
      value: 62.77477477477477
    - type: dot_f1_threshold
      value: 95.54683566093445
    - type: dot_precision
      value: 46.52777777777778
    - type: dot_recall
      value: 96.4562569213732
    - type: euclidean_accuracy
      value: 61.0
    - type: euclidean_accuracy_threshold
      value: 10.301996022462845
    - type: euclidean_ap
      value: 60.596589949359995
    - type: euclidean_f1
      value: 62.77477477477477
    - type: euclidean_f1_threshold
      value: 29.843494296073914
    - type: euclidean_precision
      value: 46.52777777777778
    - type: euclidean_recall
      value: 96.4562569213732
    - type: main_score
      value: 60.81315897987771
    - type: manhattan_accuracy
      value: 61.1
    - type: manhattan_accuracy_threshold
      value: 241.11316204071045
    - type: manhattan_ap
      value: 60.81315897987771
    - type: manhattan_f1
      value: 62.80575539568345
    - type: manhattan_f1_threshold
      value: 701.3707160949707
    - type: manhattan_precision
      value: 46.510388918486946
    - type: manhattan_recall
      value: 96.67774086378738
    - type: max_ap
      value: 60.81315897987771
    - type: max_f1
      value: 62.80575539568345
    - type: max_precision
      value: 46.52777777777778
    - type: max_recall
      value: 96.67774086378738
    - type: similarity_accuracy
      value: 61.0
    - type: similarity_accuracy_threshold
      value: 99.4693398475647
    - type: similarity_ap
      value: 60.596634996072794
    - type: similarity_f1
      value: 62.77477477477477
    - type: similarity_f1_threshold
      value: 95.54682970046997
    - type: similarity_precision
      value: 46.52777777777778
    - type: similarity_recall
      value: 96.4562569213732
  - task:
      type: STS
    dataset:
      name: MTEB SICKFr
      type: Lajavaness/SICK-fr
      config: default
      split: test
      revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
    metrics:
    - type: cosine_pearson
      value: 80.2458052019468
    - type: cosine_spearman
      value: 76.90282547383322
    - type: euclidean_pearson
      value: 76.96025494858225
    - type: euclidean_spearman
      value: 76.90369875962587
    - type: main_score
      value: 76.90282547383322
    - type: manhattan_pearson
      value: 76.96191769993092
    - type: manhattan_spearman
      value: 76.78368027265795
    - type: pearson
      value: 80.2458052019468
    - type: spearman
      value: 76.90282547383322
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 71.8166682422511
    - type: cosine_spearman
      value: 80.753981314684
    - type: euclidean_pearson
      value: 77.26991759068049
    - type: euclidean_spearman
      value: 80.753981314684
    - type: main_score
      value: 80.753981314684
    - type: manhattan_pearson
      value: 79.8934147126028
    - type: manhattan_spearman
      value: 81.7842698600436
    - type: pearson
      value: 71.8166682422511
    - type: spearman
      value: 80.753981314684
  - 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: 59.72069019022611
    - type: cosine_spearman
      value: 66.19562370923092
    - type: euclidean_pearson
      value: 60.38869296832584
    - type: euclidean_spearman
      value: 66.19562370923092
    - type: main_score
      value: 66.19562370923092
    - type: manhattan_pearson
      value: 60.735818878018044
    - type: manhattan_spearman
      value: 66.3310023111313
    - type: pearson
      value: 59.72069019022611
    - type: spearman
      value: 66.19562370923092
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
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      value: 90.73440998579521
    - type: cosine_spearman
      value: 84.51542547285167
    - type: euclidean_pearson
      value: 90.27154868530998
    - type: euclidean_spearman
      value: 84.51542547285167
    - type: main_score
      value: 84.51542547285167
    - type: manhattan_pearson
      value: 89.71184089391063
    - type: manhattan_spearman
      value: 84.51542547285167
    - type: pearson
      value: 90.73440998579521
    - type: spearman
      value: 84.51542547285167
    - type: cosine_pearson
      value: 90.73440998579521
    - type: cosine_spearman
      value: 84.51542547285167
    - type: euclidean_pearson
      value: 90.27154868530998
    - type: euclidean_spearman
      value: 84.51542547285167
    - type: main_score
      value: 84.51542547285167
    - type: manhattan_pearson
      value: 89.71184089391063
    - type: manhattan_spearman
      value: 84.51542547285167
    - type: pearson
      value: 90.73440998579521
    - type: spearman
      value: 84.51542547285167
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (fr)
      type: mteb/stsb_multi_mt
      config: fr
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 79.50928730728984
    - type: cosine_spearman
      value: 80.0932172585886
    - type: euclidean_pearson
      value: 78.52408843163009
    - type: euclidean_spearman
      value: 80.09288222088635
    - type: main_score
      value: 80.0932172585886
    - type: manhattan_pearson
      value: 78.48826046695687
    - type: manhattan_spearman
      value: 80.02496924199357
    - type: pearson
      value: 79.50928730728984
    - type: spearman
      value: 80.0932172585886
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEvalFr
      type: lyon-nlp/summarization-summeval-fr-p2p
      config: default
      split: test
      revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
    metrics:
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      value: 31.635895833264797
    - type: cosine_spearman
      value: 29.316197375472907
    - type: dot_pearson
      value: 31.635903578046314
    - type: dot_spearman
      value: 29.320397860238174
    - type: main_score
      value: 29.316197375472907
    - type: pearson
      value: 31.635895833264797
    - type: spearman
      value: 29.316197375472907
  - task:
      type: Reranking
    dataset:
      name: MTEB SyntecReranking
      type: lyon-nlp/mteb-fr-reranking-syntec-s2p
      config: default
      split: test
      revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad
    metrics:
    - type: main_score
      value: 85.96785714285713
    - type: map
      value: 85.96785714285713
    - type: mrr
      value: 85.96785714285713
    - type: nAUC_map_diff1
      value: 62.8939499970397
    - type: nAUC_map_max
      value: 17.78395289837277
    - type: nAUC_map_std
      value: 42.06945307317201
    - type: nAUC_mrr_diff1
      value: 62.8939499970397
    - type: nAUC_mrr_max
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    - type: nAUC_mrr_std
      value: 42.06945307317201
  - task:
      type: Retrieval
    dataset:
      name: MTEB SyntecRetrieval
      type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
      config: default
      split: test
      revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9
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      value: 81.745
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    - type: map_at_10
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    - type: map_at_100
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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
      value: 63.0
    - 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_5
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    - type: ndcg_at_1
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    - type: ndcg_at_10
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    - type: ndcg_at_100
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    - type: ndcg_at_1000
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    - type: ndcg_at_20
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    - type: ndcg_at_3
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    - type: ndcg_at_5
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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_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_3
      value: 91.0
    - type: recall_at_5
      value: 96.0
  - task:
      type: Retrieval
    dataset:
      name: MTEB XPQARetrieval (fr)
      type: jinaai/xpqa
      config: fra-fra
      split: test
      revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
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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: mrr_at_1
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    - type: mrr_at_100
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    - type: mrr_at_1000
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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: 53.359840954274354
  - 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: map_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
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    - type: recall_at_100
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    - type: recall_at_1000
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    - 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
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    - type: f1
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    - type: f1_weighted
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    - type: main_score
      value: 64.36999999999999
  - 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: 87.1
    - type: cosine_accuracy_threshold
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    - type: cosine_ap
      value: 67.39921410443071
    - type: cosine_f1
      value: 61.408450704225345
    - type: cosine_f1_threshold
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    - type: cosine_precision
      value: 66.06060606060606
    - type: cosine_recall
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    - type: dot_accuracy
      value: 87.1
    - type: dot_accuracy_threshold
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    - type: dot_ap
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    - type: dot_f1
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    - type: dot_f1_threshold
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    - type: dot_precision
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    - type: dot_recall
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    - type: euclidean_accuracy
      value: 87.1
    - type: euclidean_accuracy_threshold
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    - type: euclidean_ap
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    - type: euclidean_f1
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    - type: euclidean_f1_threshold
      value: 26.67142152786255
    - type: euclidean_precision
      value: 66.06060606060606
    - type: euclidean_recall
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    - type: main_score
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    - type: manhattan_accuracy
      value: 87.4
    - type: manhattan_accuracy_threshold
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    - type: manhattan_ap
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    - type: manhattan_f1
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    - 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
      value: 87.1
    - 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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  - 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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    - type: spearman
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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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    - type: mrr_at_100
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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: clarin-knext/nq-pl
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  - task:
      type: Classification
    dataset:
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      type: laugustyniak/abusive-clauses-pl
      config: default
      split: test
      revision: fc69d1c153a8ccdcf1eef52f4e2a27f88782f543
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  - task:
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      type: PL-MTEB/psc-pairclassification
      config: default
      split: test
      revision: d05a294af9e1d3ff2bfb6b714e08a24a6cabc669
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  - task:
      type: Classification
    dataset:
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      type: PL-MTEB/polemo2_in
      config: default
      split: test
      revision: d90724373c70959f17d2331ad51fb60c71176b03
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  - task:
      type: Classification
    dataset:
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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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    dataset:
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      type: clarin-knext/quora-pl
      config: default
      split: test
      revision: 0be27e93455051e531182b85e85e425aba12e9d4
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  - task:
      type: Retrieval
    dataset:
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      type: clarin-knext/scidocs-pl
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      split: test
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      value: 28.33574712082385
    - type: nauc_recall_at_5_std
      value: 16.400242628056912
    - type: ndcg_at_1
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    - type: ndcg_at_10
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    - type: ndcg_at_100
      value: 20.485999999999997
    - type: ndcg_at_1000
      value: 25.72
    - type: ndcg_at_20
      value: 16.297
    - type: ndcg_at_3
      value: 13.145000000000001
    - type: ndcg_at_5
      value: 11.413
    - type: precision_at_1
      value: 15.6
    - type: precision_at_10
      value: 7.290000000000001
    - type: precision_at_100
      value: 1.67
    - type: precision_at_1000
      value: 0.293
    - type: precision_at_20
      value: 5.025
    - type: precision_at_3
      value: 12.4
    - type: precision_at_5
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    - type: recall_at_1
      value: 3.1649999999999996
    - type: recall_at_10
      value: 14.798
    - type: recall_at_100
      value: 33.967999999999996
    - type: recall_at_1000
      value: 59.577999999999996
    - type: recall_at_20
      value: 20.403
    - type: recall_at_3
      value: 7.568
    - type: recall_at_5
      value: 10.218
  - 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: 77.82307378719935
    - type: cosine_accuracy_threshold
      value: 97.00007438659668
    - type: cosine_ap
      value: 62.95127012761914
    - type: cosine_f1
      value: 60.530590146183
    - type: cosine_f1_threshold
      value: 94.09935474395752
    - type: cosine_precision
      value: 48.82096069868996
    - type: cosine_recall
      value: 79.62962962962963
    - type: dot_accuracy
      value: 77.82307378719935
    - type: dot_accuracy_threshold
      value: 97.00008034706116
    - type: dot_ap
      value: 62.95087763566891
    - type: dot_f1
      value: 60.530590146183
    - type: dot_f1_threshold
      value: 94.099360704422
    - type: dot_precision
      value: 48.82096069868996
    - type: dot_recall
      value: 79.62962962962963
    - type: euclidean_accuracy
      value: 77.82307378719935
    - type: euclidean_accuracy_threshold
      value: 24.494586884975433
    - type: euclidean_ap
      value: 62.95127012761915
    - type: euclidean_f1
      value: 60.530590146183
    - type: euclidean_f1_threshold
      value: 34.3529999256134
    - type: euclidean_precision
      value: 48.82096069868996
    - type: euclidean_recall
      value: 79.62962962962963
    - type: main_score
      value: 62.95127012761915
    - type: manhattan_accuracy
      value: 77.6600081532817
    - type: manhattan_accuracy_threshold
      value: 569.0948009490967
    - type: manhattan_ap
      value: 62.59417668418388
    - type: manhattan_f1
      value: 60.486737763193865
    - type: manhattan_f1_threshold
      value: 803.2670974731445
    - type: manhattan_precision
      value: 49.090102086107414
    - type: manhattan_recall
      value: 78.77492877492878
    - type: max_ap
      value: 62.95127012761915
    - type: max_f1
      value: 60.530590146183
    - type: max_precision
      value: 49.090102086107414
    - type: max_recall
      value: 79.62962962962963
    - type: similarity_accuracy
      value: 77.82307378719935
    - type: similarity_accuracy_threshold
      value: 97.00007438659668
    - type: similarity_ap
      value: 62.95127012761914
    - type: similarity_f1
      value: 60.530590146183
    - type: similarity_f1_threshold
      value: 94.09935474395752
    - type: similarity_precision
      value: 48.82096069868996
    - type: similarity_recall
      value: 79.62962962962963
  - 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: 72.0298956351125
    - type: cosine_spearman
      value: 66.17464577596678
    - type: euclidean_pearson
      value: 68.98291370252295
    - type: euclidean_spearman
      value: 66.17463716306638
    - type: main_score
      value: 66.17464577596678
    - type: manhattan_pearson
      value: 68.81382804554632
    - type: manhattan_spearman
      value: 65.97651341583767
    - type: pearson
      value: 72.0298956351125
    - type: spearman
      value: 66.17464577596678
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 41.189800700866094
    - type: cosine_spearman
      value: 45.34202672993038
    - type: euclidean_pearson
      value: 27.19960620267402
    - type: euclidean_spearman
      value: 45.34202672993038
    - type: main_score
      value: 45.34202672993038
    - type: manhattan_pearson
      value: 26.949544922651196
    - type: manhattan_spearman
      value: 45.21613651872827
    - type: pearson
      value: 41.189800700866094
    - type: spearman
      value: 45.34202672993038
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
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      value: 41.459968983462765
    - type: cosine_spearman
      value: 53.581740089351996
    - type: euclidean_pearson
      value: 43.45992137124784
    - type: euclidean_spearman
      value: 53.581740089351996
    - type: main_score
      value: 53.581740089351996
    - type: manhattan_pearson
      value: 43.14606772261321
    - type: manhattan_spearman
      value: 53.181416743856836
    - type: pearson
      value: 41.459968983462765
    - type: spearman
      value: 53.581740089351996
  - 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: 60.526
    - type: map_at_1
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    - type: map_at_10
      value: 55.991
    - type: map_at_100
      value: 56.736
    - type: map_at_1000
      value: 56.8
    - type: map_at_20
      value: 56.547000000000004
    - type: map_at_3
      value: 53.603
    - type: map_at_5
      value: 54.913000000000004
    - type: mrr_at_1
      value: 49.0
    - type: mrr_at_10
      value: 57.2739417989418
    - type: mrr_at_100
      value: 57.853315794381885
    - type: mrr_at_1000
      value: 57.91488615065038
    - type: mrr_at_20
      value: 57.701351990516095
    - type: mrr_at_3
      value: 55.44444444444445
    - type: mrr_at_5
      value: 56.42777777777778
    - type: nauc_map_at_1000_diff1
      value: 57.35372319475057
    - type: nauc_map_at_1000_max
      value: 43.875320768732436
    - type: nauc_map_at_1000_std
      value: 13.322022193655078
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      value: 57.313891527698644
    - type: nauc_map_at_100_max
      value: 43.872731261320574
    - type: nauc_map_at_100_std
      value: 13.326500791745696
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      value: 57.39836451111907
    - type: nauc_map_at_10_max
      value: 43.526572478876574
    - type: nauc_map_at_10_std
      value: 12.985890578763163
    - type: nauc_map_at_1_diff1
      value: 63.12715359944983
    - type: nauc_map_at_1_max
      value: 37.86501536906817
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      value: 6.322678498743812
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      value: 57.34518997447502
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      value: 43.98066371339034
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      value: 13.295989078438582
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      value: 58.349640442692106
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      value: 43.61371135332669
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      value: 12.624087711546398
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      value: 57.60916401452899
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      value: 43.393670573290564
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      value: 12.734291845594658
    - type: nauc_mrr_at_1000_diff1
      value: 56.86336995088208
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      value: 44.16063126157464
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      value: 14.46809986588675
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      value: 56.82713594496301
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      value: 44.15947777871654
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      value: 14.468630477543204
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      value: 56.75309318959002
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      value: 44.07955977542136
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      value: 14.364429809429623
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      value: 61.55378221555377
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      value: 40.56404604782708
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      value: 11.237989014734051
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      value: 56.820233285042356
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      value: 44.273215159882724
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      value: 14.457019833008061
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      value: 57.25776927599811
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      value: 44.85862445501357
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      value: 15.08481264828146
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      value: 56.77734628869654
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      value: 44.228014048290945
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      value: 14.560343015151084
    - type: nauc_ndcg_at_1000_diff1
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    - type: nauc_ndcg_at_1000_std
      value: 15.507347464297675
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      value: 45.18506685496001
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      value: 13.918171530733483
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      value: 40.56404604782708
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      value: 11.237989014734051
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      value: 14.919203799084935
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      value: 56.27751882008217
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      value: 45.65587414820722
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      value: 14.994891252809934
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      value: 55.53169392843657
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      value: 44.23153109548333
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      value: 13.938058808850082
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      value: 39.74539590936092
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      value: 47.33091823598092
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      value: 25.97270398234439
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      value: 42.906811554469954
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      value: 25.673969211341785
    - type: nauc_recall_at_1000_diff1
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      value: 70.79831932773095
    - type: nauc_recall_at_1000_std
      value: 85.23576097105469
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      value: 43.528295808426066
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      value: 51.37810072663499
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      value: 28.73429502093998
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      value: 46.428201019869604
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      value: 43.55728664156955
    - type: nauc_recall_at_10_std
      value: 13.44915034828845
    - type: nauc_recall_at_1_diff1
      value: 63.12715359944983
    - type: nauc_recall_at_1_max
      value: 37.86501536906817
    - type: nauc_recall_at_1_std
      value: 6.322678498743812
    - type: nauc_recall_at_20_diff1
      value: 46.569137618158344
    - type: nauc_recall_at_20_max
      value: 53.92571049318345
    - type: nauc_recall_at_20_std
      value: 19.731744586272395
    - type: nauc_recall_at_3_diff1
      value: 51.783556556783786
    - type: nauc_recall_at_3_max
      value: 46.66691776547845
    - type: nauc_recall_at_3_std
      value: 16.374424975237936
    - type: nauc_recall_at_5_diff1
      value: 48.59699452539875
    - type: nauc_recall_at_5_max
      value: 43.94693563083851
    - type: nauc_recall_at_5_std
      value: 14.447872758117455
    - type: ndcg_at_1
      value: 49.0
    - type: ndcg_at_10
      value: 60.526
    - type: ndcg_at_100
      value: 63.583999999999996
    - type: ndcg_at_1000
      value: 65.017
    - type: ndcg_at_20
      value: 62.297999999999995
    - type: ndcg_at_3
      value: 56.345
    - type: ndcg_at_5
      value: 58.179
    - type: precision_at_1
      value: 49.0
    - type: precision_at_10
      value: 8.3
    - type: precision_at_100
      value: 0.993
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_20
      value: 4.567
    - type: precision_at_3
      value: 22.556
    - type: precision_at_5
      value: 14.799999999999999
    - type: recall_at_1
      value: 46.400000000000006
    - type: recall_at_10
      value: 73.161
    - type: recall_at_100
      value: 86.5
    - type: recall_at_1000
      value: 97.333
    - type: recall_at_20
      value: 79.756
    - type: recall_at_3
      value: 61.533
    - type: recall_at_5
      value: 66.22200000000001
  - 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: 65.563
    - type: map_at_1
      value: 0.22100000000000003
    - type: map_at_10
      value: 1.635
    - type: map_at_100
      value: 8.618
    - type: map_at_1000
      value: 20.422
    - type: map_at_20
      value: 2.789
    - type: map_at_3
      value: 0.609
    - type: map_at_5
      value: 0.9249999999999999
    - type: mrr_at_1
      value: 82.0
    - type: mrr_at_10
      value: 88.50000000000001
    - type: mrr_at_100
      value: 88.50000000000001
    - type: mrr_at_1000
      value: 88.50000000000001
    - type: mrr_at_20
      value: 88.50000000000001
    - type: mrr_at_3
      value: 87.66666666666667
    - type: mrr_at_5
      value: 88.16666666666667
    - type: nauc_map_at_1000_diff1
      value: -25.967067965482478
    - type: nauc_map_at_1000_max
      value: 72.92874918094974
    - type: nauc_map_at_1000_std
      value: 84.9616839707479
    - type: nauc_map_at_100_diff1
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  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB CEDRClassification
      type: ai-forever/cedr-classification
      config: default
      split: test
      revision: c0ba03d058e3e1b2f3fd20518875a4563dd12db4
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    - type: lrap
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    - type: main_score
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  - task:
      type: Classification
    dataset:
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      type: ai-forever/georeview-classification
      config: default
      split: test
      revision: 3765c0d1de6b7d264bc459433c45e5a75513839c
    metrics:
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    - type: f1
      value: 47.10882921865018
    - type: f1_weighted
      value: 47.10602639734162
    - type: main_score
      value: 51.50390625
  - task:
      type: Clustering
    dataset:
      name: MTEB GeoreviewClusteringP2P
      type: ai-forever/georeview-clustering-p2p
      config: default
      split: test
      revision: 97a313c8fc85b47f13f33e7e9a95c1ad888c7fec
    metrics:
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      value: 60.763743799017725
    - type: v_measure
      value: 60.763743799017725
    - type: v_measure_std
      value: 0.6572810824719637
  - task:
      type: Classification
    dataset:
      name: MTEB HeadlineClassification
      type: ai-forever/headline-classification
      config: default
      split: test
      revision: 2fe05ee6b5832cda29f2ef7aaad7b7fe6a3609eb
    metrics:
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    - type: f1
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    - type: f1_weighted
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    - type: main_score
      value: 84.365234375
  - task:
      type: Classification
    dataset:
      name: MTEB InappropriatenessClassification
      type: ai-forever/inappropriateness-classification
      config: default
      split: test
      revision: 601651fdc45ef243751676e62dd7a19f491c0285
    metrics:
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      value: 65.888671875
    - type: ap
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    - type: ap_weighted
      value: 60.9135452326786
    - type: f1
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    - type: f1_weighted
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    - type: main_score
      value: 65.888671875
  - task:
      type: Classification
    dataset:
      name: MTEB KinopoiskClassification
      type: ai-forever/kinopoisk-sentiment-classification
      config: default
      split: test
      revision: 5911f26666ac11af46cb9c6849d0dc80a378af24
    metrics:
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      value: 62.28666666666667
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    - type: main_score
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  - task:
      type: Reranking
    dataset:
      name: MTEB MIRACLReranking (ru)
      type: miracl/mmteb-miracl-reranking
      config: ru
      split: dev
      revision: 6d1962c527217f8927fca80f890f14f36b2802af
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      value: 49.463
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      value: 15.028
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      value: 67.67
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      value: 79.952
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      value: 74.409
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    dataset:
      name: MTEB MIRACLRetrieval (ru)
      type: miracl/mmteb-miracl
      config: ru
      split: dev
      revision: main
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  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ru)
      type: mteb/amazon_massive_intent
      config: ru
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
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  - task:
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    dataset:
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      type: mteb/amazon_massive_scenario
      config: ru
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
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    - type: main_score
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  - task:
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      type: merionum/ru_paraphraser
      config: default
      split: test
      revision: 43265056790b8f7c59e0139acb4be0a8dad2c8f4
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  - task:
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      type: ai-forever/ria-news-retrieval
      config: default
      split: test
      revision: 82374b0bbacda6114f39ff9c5b925fa1512ca5d7
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    - type: nauc_recall_at_20_std
      value: 6.8641181962978965
    - type: nauc_recall_at_3_diff1
      value: 66.82214623213184
    - type: nauc_recall_at_3_max
      value: 28.630178379853145
    - type: nauc_recall_at_3_std
      value: -10.178526591761056
    - type: nauc_recall_at_5_diff1
      value: 65.45372225751966
    - type: nauc_recall_at_5_max
      value: 30.710864571624015
    - type: nauc_recall_at_5_std
      value: -7.573418807596015
    - type: ndcg_at_1
      value: 65.97
    - type: ndcg_at_10
      value: 78.172
    - type: ndcg_at_100
      value: 79.63799999999999
    - type: ndcg_at_1000
      value: 79.915
    - type: ndcg_at_20
      value: 78.949
    - type: ndcg_at_3
      value: 75.304
    - type: ndcg_at_5
      value: 76.924
    - type: precision_at_1
      value: 65.97
    - type: precision_at_10
      value: 8.948
    - type: precision_at_100
      value: 0.962
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_20
      value: 4.626
    - type: precision_at_3
      value: 27.247
    - type: precision_at_5
      value: 17.136000000000003
    - type: recall_at_1
      value: 65.97
    - type: recall_at_10
      value: 89.48
    - type: recall_at_100
      value: 96.17999999999999
    - type: recall_at_1000
      value: 98.37
    - type: recall_at_20
      value: 92.52
    - type: recall_at_3
      value: 81.74
    - type: recall_at_5
      value: 85.68
  - task:
      type: Reranking
    dataset:
      name: MTEB RuBQReranking
      type: ai-forever/rubq-reranking
      config: default
      split: test
      revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2
    metrics:
    - type: main_score
      value: 70.23399911521713
    - type: map
      value: 70.23399911521713
    - type: mrr
      value: 75.79756531884192
    - type: nAUC_map_diff1
      value: 41.70907433488097
    - type: nAUC_map_max
      value: 19.038198833852398
    - type: nAUC_map_std
      value: 9.364787080049835
    - type: nAUC_mrr_diff1
      value: 45.427118778337864
    - type: nAUC_mrr_max
      value: 23.422465198632338
    - type: nAUC_mrr_std
      value: 12.352254802172363
  - task:
      type: Retrieval
    dataset:
      name: MTEB RuBQRetrieval
      type: ai-forever/rubq-retrieval
      config: default
      split: test
      revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b
    metrics:
    - type: main_score
      value: 67.97800000000001
    - type: map_at_1
      value: 38.682
    - type: map_at_10
      value: 59.602999999999994
    - type: map_at_100
      value: 60.609
    - type: map_at_1000
      value: 60.638999999999996
    - type: map_at_20
      value: 60.295
    - type: map_at_3
      value: 53.864000000000004
    - type: map_at_5
      value: 57.357
    - type: mrr_at_1
      value: 55.43735224586288
    - type: mrr_at_10
      value: 68.11629892303657
    - type: mrr_at_100
      value: 68.46735935081414
    - type: mrr_at_1000
      value: 68.47375950539598
    - type: mrr_at_20
      value: 68.3555220700062
    - type: mrr_at_3
      value: 65.64223798266359
    - type: mrr_at_5
      value: 67.26457840819555
    - type: nauc_map_at_1000_diff1
      value: 38.947165927647895
    - type: nauc_map_at_1000_max
      value: 21.0400498401016
    - type: nauc_map_at_1000_std
      value: -12.325977772218819
    - type: nauc_map_at_100_diff1
      value: 38.93708131706777
    - type: nauc_map_at_100_max
      value: 21.05313115659324
    - type: nauc_map_at_100_std
      value: -12.307766320896842
    - type: nauc_map_at_10_diff1
      value: 38.62500444502093
    - type: nauc_map_at_10_max
      value: 20.841336922136993
    - type: nauc_map_at_10_std
      value: -12.753687299190014
    - type: nauc_map_at_1_diff1
      value: 42.42534428928902
    - type: nauc_map_at_1_max
      value: 12.831550041111084
    - type: nauc_map_at_1_std
      value: -11.266929686927616
    - type: nauc_map_at_20_diff1
      value: 38.839757385230854
    - type: nauc_map_at_20_max
      value: 21.155443051360105
    - type: nauc_map_at_20_std
      value: -12.290324296540298
    - type: nauc_map_at_3_diff1
      value: 38.600886947896804
    - type: nauc_map_at_3_max
      value: 18.67062373078893
    - type: nauc_map_at_3_std
      value: -14.47069134931124
    - type: nauc_map_at_5_diff1
      value: 38.47519630592911
    - type: nauc_map_at_5_max
      value: 19.424230739972682
    - type: nauc_map_at_5_std
      value: -13.715848064929636
    - type: nauc_mrr_at_1000_diff1
      value: 45.829087222671134
    - type: nauc_mrr_at_1000_max
      value: 24.0611740840992
    - type: nauc_mrr_at_1000_std
      value: -13.779501374204361
    - type: nauc_mrr_at_100_diff1
      value: 45.82511154142628
    - type: nauc_mrr_at_100_max
      value: 24.068094029026092
    - type: nauc_mrr_at_100_std
      value: -13.771488599042799
    - type: nauc_mrr_at_10_diff1
      value: 45.66670841729006
    - type: nauc_mrr_at_10_max
      value: 24.21302734762609
    - type: nauc_mrr_at_10_std
      value: -13.878591942488693
    - type: nauc_mrr_at_1_diff1
      value: 49.10187561048428
    - type: nauc_mrr_at_1_max
      value: 21.468296250291164
    - type: nauc_mrr_at_1_std
      value: -14.16579631922114
    - type: nauc_mrr_at_20_diff1
      value: 45.780763156949334
    - type: nauc_mrr_at_20_max
      value: 24.16790762743539
    - type: nauc_mrr_at_20_std
      value: -13.798341816508907
    - type: nauc_mrr_at_3_diff1
      value: 45.81750015144424
    - type: nauc_mrr_at_3_max
      value: 23.74635317348391
    - type: nauc_mrr_at_3_std
      value: -14.465609504516872
    - type: nauc_mrr_at_5_diff1
      value: 45.50087795737209
    - type: nauc_mrr_at_5_max
      value: 24.021128950654578
    - type: nauc_mrr_at_5_std
      value: -14.316147652867976
    - type: nauc_ndcg_at_1000_diff1
      value: 39.98481177488298
    - type: nauc_ndcg_at_1000_max
      value: 23.50673478711865
    - type: nauc_ndcg_at_1000_std
      value: -11.112473477484098
    - type: nauc_ndcg_at_100_diff1
      value: 39.56224231830938
    - type: nauc_ndcg_at_100_max
      value: 23.886442622042228
    - type: nauc_ndcg_at_100_std
      value: -10.534435913119328
    - type: nauc_ndcg_at_10_diff1
      value: 38.438066883020696
    - type: nauc_ndcg_at_10_max
      value: 23.871323754524052
    - type: nauc_ndcg_at_10_std
      value: -12.020382617526508
    - type: nauc_ndcg_at_1_diff1
      value: 49.24897980869228
    - type: nauc_ndcg_at_1_max
      value: 21.476485407508953
    - type: nauc_ndcg_at_1_std
      value: -14.362366603555893
    - type: nauc_ndcg_at_20_diff1
      value: 39.044984412751454
    - type: nauc_ndcg_at_20_max
      value: 24.627000563476837
    - type: nauc_ndcg_at_20_std
      value: -10.591144903278847
    - type: nauc_ndcg_at_3_diff1
      value: 38.59706175845992
    - type: nauc_ndcg_at_3_max
      value: 20.660682570744303
    - type: nauc_ndcg_at_3_std
      value: -14.989842570951817
    - type: nauc_ndcg_at_5_diff1
      value: 37.99262057687399
    - type: nauc_ndcg_at_5_max
      value: 21.323357059546723
    - type: nauc_ndcg_at_5_std
      value: -13.985440057708725
    - type: nauc_precision_at_1000_diff1
      value: -7.055913327014856
    - type: nauc_precision_at_1000_max
      value: 7.645796200601874
    - type: nauc_precision_at_1000_std
      value: 5.7441793819913425
    - type: nauc_precision_at_100_diff1
      value: -5.9521730506691695
    - type: nauc_precision_at_100_max
      value: 10.791705567977127
    - type: nauc_precision_at_100_std
      value: 6.971621413042414
    - type: nauc_precision_at_10_diff1
      value: 1.2124462289393534
    - type: nauc_precision_at_10_max
      value: 17.288772868206426
    - type: nauc_precision_at_10_std
      value: 1.7066485280331372
    - type: nauc_precision_at_1_diff1
      value: 49.24897980869228
    - type: nauc_precision_at_1_max
      value: 21.476485407508953
    - type: nauc_precision_at_1_std
      value: -14.362366603555893
    - type: nauc_precision_at_20_diff1
      value: -1.9829512286324857
    - type: nauc_precision_at_20_max
      value: 15.73212540041351
    - type: nauc_precision_at_20_std
      value: 5.881638156347814
    - type: nauc_precision_at_3_diff1
      value: 15.295884096855977
    - type: nauc_precision_at_3_max
      value: 20.315378698666457
    - type: nauc_precision_at_3_std
      value: -9.87038943277974
    - type: nauc_precision_at_5_diff1
      value: 7.500406876014883
    - type: nauc_precision_at_5_max
      value: 17.81994110188596
    - type: nauc_precision_at_5_std
      value: -4.56852626899763
    - type: nauc_recall_at_1000_diff1
      value: 24.05686791288483
    - type: nauc_recall_at_1000_max
      value: 60.34558482395768
    - type: nauc_recall_at_1000_std
      value: 75.24495489488791
    - type: nauc_recall_at_100_diff1
      value: 14.41757817770598
    - type: nauc_recall_at_100_max
      value: 43.46467354926512
    - type: nauc_recall_at_100_std
      value: 33.594674489620495
    - type: nauc_recall_at_10_diff1
      value: 22.768211257001038
    - type: nauc_recall_at_10_max
      value: 29.59352351340424
    - type: nauc_recall_at_10_std
      value: -5.643974726375464
    - type: nauc_recall_at_1_diff1
      value: 42.42534428928902
    - type: nauc_recall_at_1_max
      value: 12.831550041111084
    - type: nauc_recall_at_1_std
      value: -11.266929686927616
    - type: nauc_recall_at_20_diff1
      value: 22.091666169938616
    - type: nauc_recall_at_20_max
      value: 38.1442003173532
    - type: nauc_recall_at_20_std
      value: 6.8939344221023795
    - type: nauc_recall_at_3_diff1
      value: 30.141208429704356
    - type: nauc_recall_at_3_max
      value: 19.02721767063729
    - type: nauc_recall_at_3_std
      value: -15.298243677583443
    - type: nauc_recall_at_5_diff1
      value: 25.13257041212021
    - type: nauc_recall_at_5_max
      value: 19.760375951283518
    - type: nauc_recall_at_5_std
      value: -12.907639506550343
    - type: ndcg_at_1
      value: 55.37800000000001
    - type: ndcg_at_10
      value: 67.97800000000001
    - type: ndcg_at_100
      value: 71.186
    - type: ndcg_at_1000
      value: 71.666
    - type: ndcg_at_20
      value: 69.70100000000001
    - type: ndcg_at_3
      value: 60.045
    - type: ndcg_at_5
      value: 64.206
    - type: precision_at_1
      value: 55.37800000000001
    - type: precision_at_10
      value: 13.694
    - type: precision_at_100
      value: 1.6
    - type: precision_at_1000
      value: 0.166
    - type: precision_at_20
      value: 7.394
    - type: precision_at_3
      value: 33.353
    - type: precision_at_5
      value: 23.629
    - type: recall_at_1
      value: 38.682
    - type: recall_at_10
      value: 83.624
    - type: recall_at_100
      value: 95.964
    - type: recall_at_1000
      value: 99.072
    - type: recall_at_20
      value: 89.334
    - type: recall_at_3
      value: 64.039
    - type: recall_at_5
      value: 73.92999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB RuReviewsClassification
      type: ai-forever/ru-reviews-classification
      config: default
      split: test
      revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a
    metrics:
    - type: accuracy
      value: 67.6953125
    - type: f1
      value: 65.90453756121588
    - type: f1_weighted
      value: 65.90276417438837
    - type: main_score
      value: 67.6953125
  - task:
      type: STS
    dataset:
      name: MTEB RuSTSBenchmarkSTS
      type: ai-forever/ru-stsbenchmark-sts
      config: default
      split: test
      revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018
    metrics:
    - type: cosine_pearson
      value: 76.29471433169448
    - type: cosine_spearman
      value: 76.87365514666403
    - type: euclidean_pearson
      value: 75.61167023011886
    - type: euclidean_spearman
      value: 76.87303787773313
    - type: main_score
      value: 76.87365514666403
    - type: manhattan_pearson
      value: 75.66392608968061
    - type: manhattan_spearman
      value: 76.92734684196252
    - type: pearson
      value: 76.29471433169448
    - type: spearman
      value: 76.87365514666403
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchGRNTIClassification
      type: ai-forever/ru-scibench-grnti-classification
      config: default
      split: test
      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
    metrics:
    - type: accuracy
      value: 62.76367187500001
    - type: f1
      value: 61.038547511485696
    - type: f1_weighted
      value: 61.05100853971954
    - type: main_score
      value: 62.76367187500001
  - 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: 58.12317505878799
    - type: v_measure
      value: 58.12317505878799
    - type: v_measure_std
      value: 0.8074216341773242
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchOECDClassification
      type: ai-forever/ru-scibench-oecd-classification
      config: default
      split: test
      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
    metrics:
    - type: accuracy
      value: 49.765625
    - type: f1
      value: 47.21576484201538
    - type: f1_weighted
      value: 47.216631424004845
    - type: main_score
      value: 49.765625
  - 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: 48.94279918311604
    - type: v_measure
      value: 48.94279918311604
    - type: v_measure_std
      value: 0.6861637451888378
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 64.72567885537859
    - type: cosine_spearman
      value: 67.02766486173321
    - type: euclidean_pearson
      value: 65.20776364711082
    - type: euclidean_spearman
      value: 67.02766486173321
    - type: main_score
      value: 67.02766486173321
    - type: manhattan_pearson
      value: 65.01652728805082
    - type: manhattan_spearman
      value: 67.01526065421112
    - type: pearson
      value: 64.72567885537859
    - type: spearman
      value: 67.02766486173321
  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB SensitiveTopicsClassification
      type: ai-forever/sensitive-topics-classification
      config: default
      split: test
      revision: 416b34a802308eac30e4192afc0ff99bb8dcc7f2
    metrics:
    - type: accuracy
      value: 31.5966796875
    - type: f1
      value: 37.51973703475147
    - type: lrap
      value: 47.855767144096504
    - type: main_score
      value: 31.5966796875
  - task:
      type: PairClassification
    dataset:
      name: MTEB TERRa
      type: ai-forever/terra-pairclassification
      config: default
      split: dev
      revision: 7b58f24536063837d644aab9a023c62199b2a612
    metrics:
    - type: cosine_accuracy
      value: 57.65472312703584
    - type: cosine_accuracy_threshold
      value: 83.7156891822815
    - type: cosine_ap
      value: 55.055463204979915
    - type: cosine_f1
      value: 67.26057906458797
    - type: cosine_f1_threshold
      value: 76.06719732284546
    - type: cosine_precision
      value: 51.01351351351351
    - type: cosine_recall
      value: 98.69281045751634
    - type: dot_accuracy
      value: 57.65472312703584
    - type: dot_accuracy_threshold
      value: 83.71570110321045
    - type: dot_ap
      value: 55.055463204979915
    - type: dot_f1
      value: 67.26057906458797
    - type: dot_f1_threshold
      value: 76.06720328330994
    - type: dot_precision
      value: 51.01351351351351
    - type: dot_recall
      value: 98.69281045751634
    - type: euclidean_accuracy
      value: 57.65472312703584
    - type: euclidean_accuracy_threshold
      value: 57.068902254104614
    - type: euclidean_ap
      value: 55.055463204979915
    - type: euclidean_f1
      value: 67.26057906458797
    - type: euclidean_f1_threshold
      value: 69.18495893478394
    - type: euclidean_precision
      value: 51.01351351351351
    - type: euclidean_recall
      value: 98.69281045751634
    - type: main_score
      value: 55.17437273876084
    - type: manhattan_accuracy
      value: 58.306188925081436
    - type: manhattan_accuracy_threshold
      value: 1299.5019912719727
    - type: manhattan_ap
      value: 55.17437273876084
    - type: manhattan_f1
      value: 67.25663716814158
    - type: manhattan_f1_threshold
      value: 1602.2712707519531
    - type: manhattan_precision
      value: 50.836120401337794
    - type: manhattan_recall
      value: 99.34640522875817
    - type: max_ap
      value: 55.17437273876084
    - type: max_f1
      value: 67.26057906458797
    - type: max_precision
      value: 51.01351351351351
    - type: max_recall
      value: 99.34640522875817
    - type: similarity_accuracy
      value: 57.65472312703584
    - type: similarity_accuracy_threshold
      value: 83.7156891822815
    - type: similarity_ap
      value: 55.055463204979915
    - type: similarity_f1
      value: 67.26057906458797
    - type: similarity_f1_threshold
      value: 76.06719732284546
    - type: similarity_precision
      value: 51.01351351351351
    - type: similarity_recall
      value: 98.69281045751634
---
-

<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)
```


## Citation
Please cite the repo if you use the model or code in this repo.

```
@article{hu2025kalm,
  title={KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model},
  author={Hu, Xinshuo and Shan, Zifei and Zhao, Xinping and Sun, Zetian and Liu, Zhenyu and Li, Dongfang and Ye, Shaolin and Wei, Xinyuan and Chen, Qian and Hu, Baotian and others},
  journal={arXiv preprint arXiv:2501.01028},
  year={2025}
}
```


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