sentence-transformers safetensors mpnet feature-extraction sentence-similarity mteb en model-index autotrain_compatible endpoints_compatible region:us
---
language: en
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: FUE-v1
  results:
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna (default)
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
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      value: 22.123
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      value: 23.69
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      value: 20.101
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  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
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    - type: map
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  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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    - type: pearson
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  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval (default)
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
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      type: CQADupstackRetrieval_is_a_combined_dataset
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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: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
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    - type: ndcg_at_1
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    - type: ndcg_at_1000
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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_10
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    - type: precision_at_100
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    - type: precision_at_1000
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    - type: precision_at_3
      value: 18.3
    - type: precision_at_5
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    - type: recall_at_1
      value: 4.547
    - type: recall_at_10
      value: 23.357
    - type: recall_at_100
      value: 51.047
    - type: recall_at_1000
      value: 80.63
    - type: recall_at_20
      value: 30.392999999999997
    - type: recall_at_3
      value: 11.161999999999999
    - type: recall_at_5
      value: 15.702
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cosine_pearson
      value: 82.89761522599564
    - type: cosine_spearman
      value: 79.61239240879378
    - type: euclidean_pearson
      value: 80.47994478833725
    - type: euclidean_spearman
      value: 79.61239321441792
    - type: main_score
      value: 79.61239240879378
    - type: manhattan_pearson
      value: 80.28255784608595
    - type: manhattan_spearman
      value: 79.40840813688955
    - type: pearson
      value: 82.89761555899388
    - type: spearman
      value: 79.6123884921359
  - task:
      type: STS
    dataset:
      name: MTEB STS12 (default)
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cosine_pearson
      value: 80.60566114110073
    - type: cosine_spearman
      value: 70.13320748146175
    - type: euclidean_pearson
      value: 77.57067368654582
    - type: euclidean_spearman
      value: 70.13314252571948
    - type: main_score
      value: 70.13320748146175
    - type: manhattan_pearson
      value: 77.29676392658962
    - type: manhattan_spearman
      value: 69.88321444641842
    - type: pearson
      value: 80.60566179532725
    - type: spearman
      value: 70.13415482313484
  - task:
      type: STS
    dataset:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cosine_pearson
      value: 78.320437342309
    - type: cosine_spearman
      value: 80.74355074851618
    - type: euclidean_pearson
      value: 80.17187362623575
    - type: euclidean_spearman
      value: 80.7435506767441
    - type: main_score
      value: 80.74355074851618
    - type: manhattan_pearson
      value: 79.88874001476627
    - type: manhattan_spearman
      value: 80.45868266096211
    - type: pearson
      value: 78.32043820850613
    - type: spearman
      value: 80.7435506767441
  - task:
      type: STS
    dataset:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cosine_pearson
      value: 79.70921389242768
    - type: cosine_spearman
      value: 76.24023668566399
    - type: euclidean_pearson
      value: 79.46251371995523
    - type: euclidean_spearman
      value: 76.24023301664893
    - type: main_score
      value: 76.24023668566399
    - type: manhattan_pearson
      value: 79.20065381375537
    - type: manhattan_spearman
      value: 76.00256203342937
    - type: pearson
      value: 79.70921366493712
    - type: spearman
      value: 76.24024123334894
  - task:
      type: STS
    dataset:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cosine_pearson
      value: 82.52746024419504
    - type: cosine_spearman
      value: 84.11623590647757
    - type: euclidean_pearson
      value: 83.48562697051246
    - type: euclidean_spearman
      value: 84.11623814887781
    - type: main_score
      value: 84.11623590647757
    - type: manhattan_pearson
      value: 83.31205342795175
    - type: manhattan_spearman
      value: 83.94265353931766
    - type: pearson
      value: 82.5274599058833
    - type: spearman
      value: 84.11622788808319
  - task:
      type: STS
    dataset:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cosine_pearson
      value: 74.82265172874041
    - type: cosine_spearman
      value: 78.4960329393101
    - type: euclidean_pearson
      value: 78.22716476239002
    - type: euclidean_spearman
      value: 78.4960329393101
    - type: main_score
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    - type: manhattan_pearson
      value: 78.05885015944702
    - type: manhattan_spearman
      value: 78.3249847702297
    - type: pearson
      value: 74.8226511407601
    - type: spearman
      value: 78.49603251582666
  - 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: 9.087713281584145
    - type: cosine_spearman
      value: 9.1279366990081
    - type: euclidean_pearson
      value: 9.117969623657645
    - type: euclidean_spearman
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    - type: main_score
      value: 9.1279366990081
    - type: manhattan_pearson
      value: 6.440301458166155
    - type: manhattan_spearman
      value: 6.5264401438882
    - type: pearson
      value: 9.087716717716269
    - type: spearman
      value: 9.1279366990081
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ko-ko)
      type: mteb/sts17-crosslingual-sts
      config: ko-ko
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 21.931422026594692
    - type: cosine_spearman
      value: 32.79923712532921
    - type: euclidean_pearson
      value: 28.93227440763988
    - type: euclidean_spearman
      value: 32.79905675768862
    - type: main_score
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    - type: manhattan_pearson
      value: 29.05113424705813
    - type: manhattan_spearman
      value: 32.79564881007963
    - type: pearson
      value: 21.931423583103467
    - type: spearman
      value: 32.798301050425714
  - 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: 30.28151988475531
    - type: cosine_spearman
      value: 28.038768547398902
    - type: euclidean_pearson
      value: 30.498915267658234
    - type: euclidean_spearman
      value: 28.038768547398902
    - type: main_score
      value: 28.038768547398902
    - type: manhattan_pearson
      value: 30.794292054714152
    - type: manhattan_spearman
      value: 28.56988926201773
    - type: pearson
      value: 30.281515394951132
    - type: spearman
      value: 28.038768547398902
  - 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: 1.103529546877178
    - type: cosine_spearman
      value: -4.344212733215535
    - type: euclidean_pearson
      value: 1.4727741337049667
    - type: euclidean_spearman
      value: -4.344212733215535
    - type: main_score
      value: -4.344212733215535
    - type: manhattan_pearson
      value: 3.066202915700401
    - type: manhattan_spearman
      value: -1.8750642080759847
    - type: pearson
      value: 1.1035283349143992
    - type: spearman
      value: -4.344212733215535
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ar-ar)
      type: mteb/sts17-crosslingual-sts
      config: ar-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 34.20639223082103
    - type: cosine_spearman
      value: 50.099745536749865
    - type: euclidean_pearson
      value: 46.672397550772246
    - type: euclidean_spearman
      value: 50.099745536749865
    - type: main_score
      value: 50.099745536749865
    - type: manhattan_pearson
      value: 46.27511641947692
    - type: manhattan_spearman
      value: 49.773911789667046
    - type: pearson
      value: 34.20638672669267
    - type: spearman
      value: 50.092555073567134
  - 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: 28.724311230307375
    - type: cosine_spearman
      value: 28.250724805661058
    - type: euclidean_pearson
      value: 28.315938847964397
    - type: euclidean_spearman
      value: 28.250724805661058
    - type: main_score
      value: 28.250724805661058
    - type: manhattan_pearson
      value: 27.674391866744763
    - type: manhattan_spearman
      value: 26.340658343374766
    - type: pearson
      value: 28.724300976547458
    - type: spearman
      value: 28.250724805661058
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-es)
      type: mteb/sts17-crosslingual-sts
      config: es-es
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 68.60948138294124
    - type: cosine_spearman
      value: 71.2644385447136
    - type: euclidean_pearson
      value: 73.24322173392738
    - type: euclidean_spearman
      value: 71.2644385447136
    - type: main_score
      value: 71.2644385447136
    - type: manhattan_pearson
      value: 72.77369507880161
    - type: manhattan_spearman
      value: 70.79274454462727
    - type: pearson
      value: 68.6094780579963
    - type: spearman
      value: 71.26563420541223
  - 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: 89.55726457989037
    - type: cosine_spearman
      value: 89.80253006361272
    - type: euclidean_pearson
      value: 89.52662858022953
    - type: euclidean_spearman
      value: 89.80253006361272
    - type: main_score
      value: 89.80253006361272
    - type: manhattan_pearson
      value: 89.515204742883
    - type: manhattan_spearman
      value: 89.85327040835446
    - type: pearson
      value: 89.5572652518414
    - type: spearman
      value: 89.80253006361272
  - 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: 35.25506119586307
    - type: cosine_spearman
      value: 34.7509473636312
    - type: euclidean_pearson
      value: 34.966513615613614
    - type: euclidean_spearman
      value: 34.7509473636312
    - type: main_score
      value: 34.7509473636312
    - type: manhattan_pearson
      value: 34.205440386931265
    - type: manhattan_spearman
      value: 34.19580186457024
    - type: pearson
      value: 35.255050728265005
    - type: spearman
      value: 34.7509473636312
  - 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: 29.15956073846505
    - type: cosine_spearman
      value: 23.4150546328063
    - type: euclidean_pearson
      value: 29.36385636868059
    - type: euclidean_spearman
      value: 23.4150546328063
    - type: main_score
      value: 23.4150546328063
    - type: manhattan_pearson
      value: 27.709164754459888
    - type: manhattan_spearman
      value: 21.483654161935416
    - type: pearson
      value: 29.159552605316065
    - type: spearman
      value: 23.4150546328063
  - 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: 16.614254117804347
    - type: cosine_spearman
      value: 17.838933806777177
    - type: euclidean_pearson
      value: 16.374166189982727
    - type: euclidean_spearman
      value: 17.838933806777177
    - type: main_score
      value: 17.838933806777177
    - type: manhattan_pearson
      value: 17.061405031678706
    - type: manhattan_spearman
      value: 17.720413541179628
    - type: pearson
      value: 16.61424897880095
    - type: spearman
      value: 17.838933806777177
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-it)
      type: mteb/sts22-crosslingual-sts
      config: es-it
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 33.923866543364184
    - type: cosine_spearman
      value: 28.270091354677568
    - type: euclidean_pearson
      value: 32.54215682097072
    - type: euclidean_spearman
      value: 28.270091354677568
    - type: main_score
      value: 28.270091354677568
    - type: manhattan_pearson
      value: 32.330367232207976
    - type: manhattan_spearman
      value: 28.255815608210906
    - type: pearson
      value: 33.923868062160935
    - type: spearman
      value: 28.270091354677568
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ar)
      type: mteb/sts22-crosslingual-sts
      config: ar
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 33.485734155602124
    - type: cosine_spearman
      value: 35.184256236066545
    - type: euclidean_pearson
      value: 35.72218023358308
    - type: euclidean_spearman
      value: 35.184256236066545
    - type: main_score
      value: 35.184256236066545
    - type: manhattan_pearson
      value: 35.6410009964212
    - type: manhattan_spearman
      value: 35.234893627175516
    - type: pearson
      value: 33.485735809605345
    - type: spearman
      value: 35.184256236066545
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de)
      type: mteb/sts22-crosslingual-sts
      config: de
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 9.234564624165541
    - type: cosine_spearman
      value: 9.26135671318589
    - type: euclidean_pearson
      value: 5.846102863095134
    - type: euclidean_spearman
      value: 9.26135671318589
    - type: main_score
      value: 9.26135671318589
    - type: manhattan_pearson
      value: 5.7129856416500635
    - type: manhattan_spearman
      value: 9.101317893245328
    - type: pearson
      value: 9.23456334729063
    - type: spearman
      value: 9.253696154102018
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 7.541720515534752
    - type: cosine_spearman
      value: 16.228492544303737
    - type: euclidean_pearson
      value: 8.688753048966332
    - type: euclidean_spearman
      value: 16.228492544303737
    - type: main_score
      value: 16.228492544303737
    - type: manhattan_pearson
      value: 8.82151603264942
    - type: manhattan_spearman
      value: 14.072905299329804
    - type: pearson
      value: 7.5417136414683394
    - type: spearman
      value: 16.228492544303737
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 14.272880349051686
    - type: cosine_spearman
      value: 26.923117280473786
    - type: euclidean_pearson
      value: 21.452060315735473
    - type: euclidean_spearman
      value: 26.923117280473786
    - type: main_score
      value: 26.923117280473786
    - type: manhattan_pearson
      value: 21.100522438025678
    - type: manhattan_spearman
      value: 26.877576505273343
    - type: pearson
      value: 14.272881506036967
    - type: spearman
      value: 26.92266584563422
  - 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: 43.299601499947705
    - type: cosine_spearman
      value: 44.906191184092506
    - type: euclidean_pearson
      value: 44.27229004756392
    - type: euclidean_spearman
      value: 44.906191184092506
    - type: main_score
      value: 44.906191184092506
    - type: manhattan_pearson
      value: 43.30226127948028
    - type: manhattan_spearman
      value: 44.15123742556422
    - type: pearson
      value: 43.29959849491429
    - type: spearman
      value: 44.906191184092506
  - 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: 38.208833040701016
    - type: cosine_spearman
      value: 40.35513412565045
    - type: euclidean_pearson
      value: 37.69713615937953
    - type: euclidean_spearman
      value: 40.35513412565045
    - type: main_score
      value: 40.35513412565045
    - type: manhattan_pearson
      value: 38.07295736531383
    - type: manhattan_spearman
      value: 41.18949838024728
    - type: pearson
      value: 38.20882899305228
    - type: spearman
      value: 40.35513412565045
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 57.64495357984024
    - type: cosine_spearman
      value: 58.654277042743985
    - type: euclidean_pearson
      value: 57.6918916487343
    - type: euclidean_spearman
      value: 58.654277042743985
    - type: main_score
      value: 58.654277042743985
    - type: manhattan_pearson
      value: 57.44807489792652
    - type: manhattan_spearman
      value: 58.55625686584207
    - type: pearson
      value: 57.64495326981972
    - type: spearman
      value: 58.654277042743985
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (tr)
      type: mteb/sts22-crosslingual-sts
      config: tr
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 11.450692016022549
    - type: cosine_spearman
      value: 17.51115938663503
    - type: euclidean_pearson
      value: 15.02321459776712
    - type: euclidean_spearman
      value: 17.51115938663503
    - type: main_score
      value: 17.51115938663503
    - type: manhattan_pearson
      value: 14.927559119791256
    - type: manhattan_spearman
      value: 17.573688652181342
    - type: pearson
      value: 11.450690790822087
    - type: spearman
      value: 17.51115938663503
  - 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: 43.813735649943744
    - type: cosine_spearman
      value: 43.21656383381947
    - type: euclidean_pearson
      value: 44.23609795164775
    - type: euclidean_spearman
      value: 43.21656383381947
    - type: main_score
      value: 43.21656383381947
    - type: manhattan_pearson
      value: 45.15245284513481
    - type: manhattan_spearman
      value: 44.617872376647036
    - type: pearson
      value: 43.81373603921556
    - type: spearman
      value: 43.21656383381947
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 2.064593579711082
    - type: cosine_spearman
      value: 13.671807943753796
    - type: euclidean_pearson
      value: -0.2014491570823139
    - type: euclidean_spearman
      value: 13.671807943753796
    - type: main_score
      value: 13.671807943753796
    - type: manhattan_pearson
      value: -0.47928238790519784
    - type: manhattan_spearman
      value: 13.539652287241891
    - type: pearson
      value: 2.064597029930494
    - type: spearman
      value: 13.877866791327195
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (it)
      type: mteb/sts22-crosslingual-sts
      config: it
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 34.34600586953367
    - type: cosine_spearman
      value: 35.333432813362556
    - type: euclidean_pearson
      value: 35.55800799947818
    - type: euclidean_spearman
      value: 35.333432813362556
    - type: main_score
      value: 35.333432813362556
    - type: manhattan_pearson
      value: 35.52036355368523
    - type: manhattan_spearman
      value: 35.32333999151806
    - type: pearson
      value: 34.34600393440248
    - type: spearman
      value: 35.333432813362556
  - 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: 34.38468852241422
    - type: cosine_spearman
      value: 37.517923206663426
    - type: euclidean_pearson
      value: 36.15747644065988
    - type: euclidean_spearman
      value: 37.517923206663426
    - type: main_score
      value: 37.517923206663426
    - type: manhattan_pearson
      value: 36.367891064808674
    - type: manhattan_spearman
      value: 36.98092141912518
    - type: pearson
      value: 34.3846838424612
    - type: spearman
      value: 37.517923206663426
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 62.10106220976315
    - type: cosine_spearman
      value: 62.162497286103665
    - type: euclidean_pearson
      value: 63.47223854069964
    - type: euclidean_spearman
      value: 62.162497286103665
    - type: main_score
      value: 62.162497286103665
    - type: manhattan_pearson
      value: 63.20260003333065
    - type: manhattan_spearman
      value: 61.91516380449414
    - type: pearson
      value: 62.10106168936663
    - type: spearman
      value: 62.162497286103665
  - 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: 43.060498443703956
    - type: cosine_spearman
      value: 46.96962646942495
    - type: euclidean_pearson
      value: 44.32895696900264
    - type: euclidean_spearman
      value: 46.96962646942495
    - type: main_score
      value: 46.96962646942495
    - type: manhattan_pearson
      value: 44.35969054771841
    - type: manhattan_spearman
      value: 47.06500736586804
    - type: pearson
      value: 43.060495996175085
    - type: spearman
      value: 46.96962646942495
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es)
      type: mteb/sts22-crosslingual-sts
      config: es
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 31.552876706984677
    - type: cosine_spearman
      value: 36.385581860846955
    - type: euclidean_pearson
      value: 35.09094631898299
    - type: euclidean_spearman
      value: 36.385581860846955
    - type: main_score
      value: 36.385581860846955
    - type: manhattan_pearson
      value: 34.90394958111092
    - type: manhattan_spearman
      value: 36.31134774911119
    - type: pearson
      value: 31.552876690362574
    - type: spearman
      value: 36.385581860846955
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 69.17422308603082
    - type: cosine_spearman
      value: 61.97797868009122
    - type: euclidean_pearson
      value: 68.87185772300731
    - type: euclidean_spearman
      value: 61.97797868009122
    - type: main_score
      value: 61.97797868009122
    - type: manhattan_pearson
      value: 69.95446576863942
    - type: manhattan_spearman
      value: 61.97797868009122
    - type: pearson
      value: 69.17420713169005
    - type: spearman
      value: 61.97797868009122
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 7.810349558361704
    - type: cosine_spearman
      value: 13.082192851727692
    - type: euclidean_pearson
      value: 9.256112073506458
    - type: euclidean_spearman
      value: 13.082192851727692
    - type: main_score
      value: 13.082192851727692
    - type: manhattan_pearson
      value: 8.72571445455125
    - type: manhattan_spearman
      value: 12.72837879957086
    - type: pearson
      value: 7.8103471976464665
    - type: spearman
      value: 13.082192851727692
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cosine_pearson
      value: 81.60094971873578
    - type: cosine_spearman
      value: 82.21497157084686
    - type: euclidean_pearson
      value: 82.7649580865935
    - type: euclidean_spearman
      value: 82.21487652663633
    - type: main_score
      value: 82.21497157084686
    - type: manhattan_pearson
      value: 82.60879748854263
    - type: manhattan_spearman
      value: 82.02680374744259
    - type: pearson
      value: 81.60094958106916
    - type: spearman
      value: 82.21497157084686
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: main_score
      value: 88.0620858216092
    - type: map
      value: 88.0620858216092
    - type: mrr
      value: 96.56171442936149
    - type: nAUC_map_diff1
      value: -10.48187303124293
    - type: nAUC_map_max
      value: 56.61425009792597
    - type: nAUC_map_std
      value: 71.46629366886685
    - type: nAUC_mrr_diff1
      value: 32.581743266040704
    - type: nAUC_mrr_max
      value: 88.42416536858423
    - type: nAUC_mrr_std
      value: 83.97838942252417
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact (default)
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: main_score
      value: 60.521
    - type: map_at_1
      value: 44.622
    - type: map_at_10
      value: 55.033
    - type: map_at_100
      value: 55.659000000000006
    - type: map_at_1000
      value: 55.701
    - type: map_at_20
      value: 55.379999999999995
    - type: map_at_3
      value: 51.918
    - type: map_at_5
      value: 53.563
    - type: mrr_at_1
      value: 46.666666666666664
    - type: mrr_at_10
      value: 56.386640211640184
    - type: mrr_at_100
      value: 56.86324391737727
    - type: mrr_at_1000
      value: 56.899770911998424
    - type: mrr_at_20
      value: 56.63502866958745
    - type: mrr_at_3
      value: 53.88888888888887
    - type: mrr_at_5
      value: 55.388888888888886
    - type: nauc_map_at_1000_diff1
      value: 60.51522831114532
    - type: nauc_map_at_1000_max
      value: 38.729857044583156
    - type: nauc_map_at_1000_std
      value: 11.893619390095981
    - type: nauc_map_at_100_diff1
      value: 60.49224806809106
    - type: nauc_map_at_100_max
      value: 38.757391171919394
    - type: nauc_map_at_100_std
      value: 11.904869622843274
    - type: nauc_map_at_10_diff1
      value: 60.59184266027688
    - type: nauc_map_at_10_max
      value: 38.814372515682855
    - type: nauc_map_at_10_std
      value: 12.062834601122749
    - type: nauc_map_at_1_diff1
      value: 65.53217534037644
    - type: nauc_map_at_1_max
      value: 28.820516516628203
    - type: nauc_map_at_1_std
      value: 0.31747544825532187
    - type: nauc_map_at_20_diff1
      value: 60.49567580134993
    - type: nauc_map_at_20_max
      value: 38.75172270044811
    - type: nauc_map_at_20_std
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  - task:
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      type: mteb/scifact
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      revision: 0228b52cf27578f30900b9e5271d331663a030d7
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  - task:
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      type: mteb/sprintduplicatequestions-pairclassification
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      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: validation
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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  - task:
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      type: mteb/stackoverflowdupquestions-reranking
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      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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  - task:
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      type: mteb/touche2020
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    - type: nauc_precision_at_1_std
      value: 1.8363187629423776
    - type: nauc_precision_at_20_diff1
      value: 14.726770245618805
    - type: nauc_precision_at_20_max
      value: -21.815069886538808
    - type: nauc_precision_at_20_std
      value: 18.892811452623157
    - type: nauc_precision_at_3_diff1
      value: 0.9886305353262563
    - type: nauc_precision_at_3_max
      value: -20.231039993615312
    - type: nauc_precision_at_3_std
      value: 6.358708074233125
    - type: nauc_precision_at_5_diff1
      value: 15.348665084122503
    - type: nauc_precision_at_5_max
      value: -23.255200414646325
    - type: nauc_precision_at_5_std
      value: 5.968161709012153
    - type: nauc_recall_at_1000_diff1
      value: 4.060744763807052
    - type: nauc_recall_at_1000_max
      value: -11.386644024112234
    - type: nauc_recall_at_1000_std
      value: 77.38341256255143
    - type: nauc_recall_at_100_diff1
      value: 3.0602490159843883
    - type: nauc_recall_at_100_max
      value: -23.133334130489928
    - type: nauc_recall_at_100_std
      value: 42.72840616542226
    - type: nauc_recall_at_10_diff1
      value: 8.794442377965375
    - type: nauc_recall_at_10_max
      value: -11.666849404762925
    - type: nauc_recall_at_10_std
      value: -7.829821703241252
    - type: nauc_recall_at_1_diff1
      value: -14.540804131417854
    - type: nauc_recall_at_1_max
      value: -5.1573008851326065
    - type: nauc_recall_at_1_std
      value: -7.656042570304873
    - type: nauc_recall_at_20_diff1
      value: 9.614735799856538
    - type: nauc_recall_at_20_max
      value: -14.765691684991822
    - type: nauc_recall_at_20_std
      value: 0.612424582124656
    - type: nauc_recall_at_3_diff1
      value: -6.910547196179005
    - type: nauc_recall_at_3_max
      value: -9.544659311113964
    - type: nauc_recall_at_3_std
      value: -5.046214274501399
    - type: nauc_recall_at_5_diff1
      value: 6.384770222182381
    - type: nauc_recall_at_5_max
      value: -19.233502105079932
    - type: nauc_recall_at_5_std
      value: -5.566077739772719
    - type: ndcg_at_1
      value: 18.367
    - type: ndcg_at_10
      value: 18.801000000000002
    - type: ndcg_at_100
      value: 30.296
    - type: ndcg_at_1000
      value: 42.018
    - type: ndcg_at_20
      value: 20.14
    - type: ndcg_at_3
      value: 20.96
    - type: ndcg_at_5
      value: 19.683999999999997
    - type: precision_at_1
      value: 20.408
    - type: precision_at_10
      value: 16.531000000000002
    - type: precision_at_100
      value: 6.49
    - type: precision_at_1000
      value: 1.443
    - type: precision_at_20
      value: 13.776
    - type: precision_at_3
      value: 22.448999999999998
    - type: precision_at_5
      value: 19.592000000000002
    - type: recall_at_1
      value: 1.522
    - type: recall_at_10
      value: 12.255
    - type: recall_at_100
      value: 41.64
    - type: recall_at_1000
      value: 77.46499999999999
    - type: recall_at_20
      value: 19.136
    - type: recall_at_3
      value: 5.113
    - type: recall_at_5
      value: 7.348000000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cosine_accuracy
      value: 86.35036061274364
    - type: cosine_accuracy_threshold
      value: 78.45808267593384
    - type: cosine_ap
      value: 74.3562958182802
    - type: cosine_f1
      value: 69.23173016864459
    - type: cosine_f1_threshold
      value: 75.69116353988647
    - type: cosine_precision
      value: 65.74139976275207
    - type: cosine_recall
      value: 73.11345646437995
    - type: dot_accuracy
      value: 86.35036061274364
    - type: dot_accuracy_threshold
      value: 78.45808267593384
    - type: dot_ap
      value: 74.35629143935617
    - type: dot_f1
      value: 69.23173016864459
    - type: dot_f1_threshold
      value: 75.69116353988647
    - type: dot_precision
      value: 65.74139976275207
    - type: dot_recall
      value: 73.11345646437995
    - type: euclidean_accuracy
      value: 86.35036061274364
    - type: euclidean_accuracy_threshold
      value: 65.63827991485596
    - type: euclidean_ap
      value: 74.35629336635377
    - type: euclidean_f1
      value: 69.23173016864459
    - type: euclidean_f1_threshold
      value: 69.72637176513672
    - type: euclidean_precision
      value: 65.74139976275207
    - type: euclidean_recall
      value: 73.11345646437995
    - type: main_score
      value: 74.3562958182802
    - type: manhattan_accuracy
      value: 86.30267628300649
    - type: manhattan_accuracy_threshold
      value: 1388.2848739624023
    - type: manhattan_ap
      value: 74.34214111115519
    - type: manhattan_f1
      value: 69.18905284399041
    - type: manhattan_f1_threshold
      value: 1506.6452026367188
    - type: manhattan_precision
      value: 66.27204638801642
    - type: manhattan_recall
      value: 72.37467018469657
    - type: max_accuracy
      value: 86.35036061274364
    - type: max_ap
      value: 74.3562958182802
    - type: max_f1
      value: 69.23173016864459
    - type: max_precision
      value: 66.27204638801642
    - type: max_recall
      value: 73.11345646437995
    - type: similarity_accuracy
      value: 86.35036061274364
    - type: similarity_accuracy_threshold
      value: 78.4580945968628
    - type: similarity_ap
      value: 74.3562875678525
    - type: similarity_f1
      value: 69.23173016864459
    - type: similarity_f1_threshold
      value: 75.69118142127991
    - type: similarity_precision
      value: 65.74139976275207
    - type: similarity_recall
      value: 73.11345646437995
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cosine_accuracy
      value: 88.15539255637054
    - type: cosine_accuracy_threshold
      value: 78.5060167312622
    - type: cosine_ap
      value: 84.15130253353578
    - type: cosine_f1
      value: 76.15275390479039
    - type: cosine_f1_threshold
      value: 75.17023086547852
    - type: cosine_precision
      value: 73.97996224771308
    - type: cosine_recall
      value: 78.45703726516786
    - type: dot_accuracy
      value: 88.15539255637054
    - type: dot_accuracy_threshold
      value: 78.50601077079773
    - type: dot_ap
      value: 84.15130163532636
    - type: dot_f1
      value: 76.15275390479039
    - type: dot_f1_threshold
      value: 75.17023086547852
    - type: dot_precision
      value: 73.97996224771308
    - type: dot_recall
      value: 78.45703726516786
    - type: euclidean_accuracy
      value: 88.15539255637054
    - type: euclidean_accuracy_threshold
      value: 65.56521654129028
    - type: euclidean_ap
      value: 84.1513046482876
    - type: euclidean_f1
      value: 76.15275390479039
    - type: euclidean_f1_threshold
      value: 70.46952247619629
    - type: euclidean_precision
      value: 73.97996224771308
    - type: euclidean_recall
      value: 78.45703726516786
    - type: main_score
      value: 84.1513046482876
    - type: manhattan_accuracy
      value: 88.13404742500097
    - type: manhattan_accuracy_threshold
      value: 1414.7026062011719
    - type: manhattan_ap
      value: 84.12376985849109
    - type: manhattan_f1
      value: 76.16659806159488
    - type: manhattan_f1_threshold
      value: 1529.8437118530273
    - type: manhattan_precision
      value: 74.09537677466326
    - type: manhattan_recall
      value: 78.35694487218971
    - type: max_accuracy
      value: 88.15539255637054
    - type: max_ap
      value: 84.1513046482876
    - type: max_f1
      value: 76.16659806159488
    - type: max_precision
      value: 74.09537677466326
    - type: max_recall
      value: 78.45703726516786
    - type: similarity_accuracy
      value: 88.15539255637054
    - type: similarity_accuracy_threshold
      value: 78.5060167312622
    - type: similarity_ap
      value: 84.15130432409686
    - type: similarity_f1
      value: 76.15275390479039
    - type: similarity_f1_threshold
      value: 75.17023086547852
    - type: similarity_precision
      value: 73.97996224771308
    - type: similarity_recall
      value: 78.45703726516786
---

# FUE

This is a sentence transformer model based on all-mpnet-base-v2.

## Usage

```python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is encoded"]

model = SentenceTransformer('FAE')
embeddings = model.encode(sentences)
print(embeddings)
```

