metadata

language: []
library_name: sentence-transformers
tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - dataset_size:100K<n<1M
  - loss:AnglELoss
base_model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
metrics:
  - pearson_cosine
  - spearman_cosine
  - pearson_manhattan
  - spearman_manhattan
  - pearson_euclidean
  - spearman_euclidean
  - pearson_dot
  - spearman_dot
  - pearson_max
  - spearman_max
widget:
  - source_sentence: 有些人在路上溜达。
    sentences:
      - Folk går
      - Otururken gitar çalan adam.
      - ארה"ב קבעה שסוריה השתמשה בנשק כימי
  - source_sentence: 緬甸以前稱為緬甸。
    sentences:
      - 缅甸以前叫缅甸。
      - This is very contradictory.
      - 한 남자가 아기를 안고 의자에 앉아 잠들어 있다.
  - source_sentence: אדם כותב.
    sentences:
      - האדם כותב.
      - questa non è una risposta.
      - 7 שוטרים נהרגו ו-4 שוטרים נפצעו.
  - source_sentence: הם מפחדים.
    sentences:
      - liên quan đến rủi ro đáng kể;
      - A man is playing a guitar.
      - A man is playing a piano.
  - source_sentence: 一个女人正在洗澡。
    sentences:
      - A woman is taking a bath.
      - En jente børster håret sitt
      - אדם מחלק תפוח אדמה.
pipeline_tag: sentence-similarity
model-index:
  - name: >-
      SentenceTransformer based on
      sentence-transformers/paraphrase-multilingual-mpnet-base-v2
    results:
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts dev
          type: sts-dev
        metrics:
          - type: pearson_cosine
            value: 0.9551466915019567
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9592676437617756
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.9270103565661432
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.9382925369644322
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.9278315400036575
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.9393641949848517
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8760113280718741
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8864509380027734
            name: Spearman Dot
          - type: pearson_max
            value: 0.9551466915019567
            name: Pearson Max
          - type: spearman_max
            value: 0.9592676437617756
            name: Spearman Max
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts test
          type: sts-test
        metrics:
          - type: pearson_cosine
            value: 0.9479585032380113
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9514910354916427
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.925192141913064
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.9351648026362221
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.9258239806908134
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.9363652577900217
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8442947652156254
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8435104766124126
            name: Spearman Dot
          - type: pearson_max
            value: 0.9479585032380113
            name: Pearson Max
          - type: spearman_max
            value: 0.9514910354916427
            name: Spearman Max
          - type: pearson_cosine
            value: 0.9725274765440489
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9766335692570665
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.9382317294386867
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.948654920505423
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.9392057529290415
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.9500099103637895
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8531236460319379
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8611492409185547
            name: Spearman Dot
          - type: pearson_max
            value: 0.9725274765440489
            name: Pearson Max
          - type: spearman_max
            value: 0.9766335692570665
            name: Spearman Max
          - type: pearson_cosine
            value: 0.8026922386812214
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.8124393788492182
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.7839394479918361
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.7899571854314883
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.7835912695413444
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.7920219916708612
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.7698701769634279
            name: Pearson Dot
          - type: spearman_dot
            value: 0.781996122357711
            name: Spearman Dot
          - type: pearson_max
            value: 0.8026922386812214
            name: Pearson Max
          - type: spearman_max
            value: 0.8124393788492182
            name: Spearman Max
          - type: pearson_cosine
            value: 0.7795928581740468
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.7703365842088069
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.7903764226370217
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.7829879213871844
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.7911863454505806
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.7841695636601043
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.7077312955932407
            name: Pearson Dot
          - type: spearman_dot
            value: 0.6914225616023565
            name: Spearman Dot
          - type: pearson_max
            value: 0.7911863454505806
            name: Pearson Max
          - type: spearman_max
            value: 0.7841695636601043
            name: Spearman Max
          - type: pearson_cosine
            value: 0.9112700251605085
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9109414091487618
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.8969826303560867
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.8934356058163047
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.8986106629139636
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.8954517657266873
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.884386067267308
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8922685778872441
            name: Spearman Dot
          - type: pearson_max
            value: 0.9112700251605085
            name: Pearson Max
          - type: spearman_max
            value: 0.9109414091487618
            name: Spearman Max
          - type: pearson_cosine
            value: 0.9361870787330656
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9378741534997558
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.9230051982649123
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.9244721677465636
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.9230904520135751
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.9251248730902872
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.9069963151228692
            name: Pearson Dot
          - type: spearman_dot
            value: 0.9185797530151516
            name: Spearman Dot
          - type: pearson_max
            value: 0.9361870787330656
            name: Pearson Max
          - type: spearman_max
            value: 0.9378741534997558
            name: Spearman Max
          - type: pearson_cosine
            value: 0.8048757108412675
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.7987027653005363
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.8017660413612523
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.7828168153285264
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.8006665075585622
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.7824761741785664
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.7894710045147775
            name: Pearson Dot
          - type: spearman_dot
            value: 0.7819409907917216
            name: Spearman Dot
          - type: pearson_max
            value: 0.8048757108412675
            name: Pearson Max
          - type: spearman_max
            value: 0.7987027653005363
            name: Spearman Max
          - type: pearson_cosine
            value: 0.8520160385093393
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.8553203530552356
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.8464006282913296
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.8409514527398295
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.8467543977447098
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.8458591066828018
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8093136598158064
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8153571493902085
            name: Spearman Dot
          - type: pearson_max
            value: 0.8520160385093393
            name: Pearson Max
          - type: spearman_max
            value: 0.8553203530552356
            name: Spearman Max
          - type: pearson_cosine
            value: 0.8751983236341568
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.872701191632785
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.8744834146908832
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.8661385734785878
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.874802989814616
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.8668384026485944
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8603441420083793
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8519571499551175
            name: Spearman Dot
          - type: pearson_max
            value: 0.8751983236341568
            name: Pearson Max
          - type: spearman_max
            value: 0.872701191632785
            name: Spearman Max
          - type: pearson_cosine
            value: 0.9082404991830442
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9067607122592818
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.8908378724095692
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.885184918244054
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.8907567800603056
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.8850799779856109
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8888621290344544
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8965880419316619
            name: Spearman Dot
          - type: pearson_max
            value: 0.9082404991830442
            name: Pearson Max
          - type: spearman_max
            value: 0.9067607122592818
            name: Spearman Max
          - type: pearson_cosine
            value: 0.9249796814520836
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9246785886944904
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.9083667986520362
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.90288714821411
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.9115880396459031
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.9083794061358542
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.9000889923763985
            name: Pearson Dot
          - type: spearman_dot
            value: 0.9070443969139744
            name: Spearman Dot
          - type: pearson_max
            value: 0.9249796814520836
            name: Pearson Max
          - type: spearman_max
            value: 0.9246785886944904
            name: Spearman Max
          - type: pearson_cosine
            value: 0.9133091498737149
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9114826394926738
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.8977113793113364
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.8933433506440468
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.8979058595014344
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.8937323599537337
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.891219202934611
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8987764114969254
            name: Spearman Dot
          - type: pearson_max
            value: 0.9133091498737149
            name: Pearson Max
          - type: spearman_max
            value: 0.9114826394926738
            name: Spearman Max
          - type: pearson_cosine
            value: 0.8984578585216539
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.8451542547285167
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.8714879175346363
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.8451542547285167
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.8809190484217423
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.8451542547285167
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.8537957222589418
            name: Pearson Dot
          - type: spearman_dot
            value: 0.8451542547285167
            name: Spearman Dot
          - type: pearson_max
            value: 0.8984578585216539
            name: Pearson Max
          - type: spearman_max
            value: 0.8451542547285167
            name: Spearman Max
          - type: pearson_cosine
            value: 0.6494815112978085
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6385354535483773
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.6429493098908716
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6473666993823523
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.6442945700268683
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.6444758519763731
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.6128358976757747
            name: Pearson Dot
          - type: spearman_dot
            value: 0.6108258021881942
            name: Spearman Dot
          - type: pearson_max
            value: 0.6494815112978085
            name: Pearson Max
          - type: spearman_max
            value: 0.6473666993823523
            name: Spearman Max
          - type: pearson_cosine
            value: 0.7441341150359049
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.7518021273920814
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.7339108684091178
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.7367402927783612
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.7336764576613932
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.734241088471987
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.6886320720189693
            name: Pearson Dot
          - type: spearman_dot
            value: 0.698561864698337
            name: Spearman Dot
          - type: pearson_max
            value: 0.7441341150359049
            name: Pearson Max
          - type: spearman_max
            value: 0.7518021273920814
            name: Spearman Max
          - type: pearson_cosine
            value: 0.6278594754203957
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6319430830291571
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.543548091135791
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6002053211770223
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.5399866615749636
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.5955360076924765
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.5657998544710718
            name: Pearson Dot
          - type: spearman_dot
            value: 0.6068611192160528
            name: Spearman Dot
          - type: pearson_max
            value: 0.6278594754203957
            name: Pearson Max
          - type: spearman_max
            value: 0.6319430830291571
            name: Spearman Max
          - type: pearson_cosine
            value: 0.7778538763931996
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.7875616631597785
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.7425757616272681
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.7789392103102715
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.7437054735775576
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.780583955651507
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.7214423493083364
            name: Pearson Dot
          - type: spearman_dot
            value: 0.7489073787091952
            name: Spearman Dot
          - type: pearson_max
            value: 0.7778538763931996
            name: Pearson Max
          - type: spearman_max
            value: 0.7875616631597785
            name: Spearman Max
          - type: pearson_cosine
            value: 0.526790729806662
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.5774252131250034
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.41713442172065224
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.5599676717727231
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.42192411421528214
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.5665444422359257
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.49809047501575476
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5367148143234142
            name: Spearman Dot
          - type: pearson_max
            value: 0.526790729806662
            name: Pearson Max
          - type: spearman_max
            value: 0.5774252131250034
            name: Spearman Max
          - type: pearson_cosine
            value: 0.6306061651851392
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6383757017928495
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.603366556372183
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6167955278711116
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.6081018686388112
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.6219639110001453
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.5767081284665276
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5831358067917275
            name: Spearman Dot
          - type: pearson_max
            value: 0.6306061651851392
            name: Pearson Max
          - type: spearman_max
            value: 0.6383757017928495
            name: Spearman Max
          - type: pearson_cosine
            value: 0.5568482062575557
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.5866853707548388
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.49244450938868833
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.5737511662255662
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.49058760093828624
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.5762095703672849
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.4306984514506903
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5470683854030187
            name: Spearman Dot
          - type: pearson_max
            value: 0.5568482062575557
            name: Pearson Max
          - type: spearman_max
            value: 0.5866853707548388
            name: Spearman Max
          - type: pearson_cosine
            value: 0.5776222742798018
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.5749790581441845
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.571787148920759
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.5500811027014174
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.5695499775959532
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.5532223379017994
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.53146407233978
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5190797374963447
            name: Spearman Dot
          - type: pearson_max
            value: 0.5776222742798018
            name: Pearson Max
          - type: spearman_max
            value: 0.5749790581441845
            name: Spearman Max
          - type: pearson_cosine
            value: 0.3571900232473057
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.4335552432730643
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.20808854264339055
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.4354537154533896
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.208616390027902
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.440246452767669
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.22336496195751424
            name: Pearson Dot
          - type: spearman_dot
            value: 0.3706905558756734
            name: Spearman Dot
          - type: pearson_max
            value: 0.3571900232473057
            name: Pearson Max
          - type: spearman_max
            value: 0.440246452767669
            name: Spearman Max
          - type: pearson_cosine
            value: 0.6863427356006826
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6620948502618977
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.6428578762643233
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6483663123081533
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.6424050032110411
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.6485902628925195
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.6352371374824808
            name: Pearson Dot
          - type: spearman_dot
            value: 0.6159110999161411
            name: Spearman Dot
          - type: pearson_max
            value: 0.6863427356006826
            name: Pearson Max
          - type: spearman_max
            value: 0.6620948502618977
            name: Spearman Max
          - type: pearson_cosine
            value: 0.7570295008280781
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.7510805416538202
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.7191097960855934
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.7140422377894933
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.7204228437397647
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.7257632200250398
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.7144336778935939
            name: Pearson Dot
          - type: spearman_dot
            value: 0.7284199759984302
            name: Spearman Dot
          - type: pearson_max
            value: 0.7570295008280781
            name: Pearson Max
          - type: spearman_max
            value: 0.7510805416538202
            name: Spearman Max
          - type: pearson_cosine
            value: 0.6502825737911098
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6624635951676386
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.647419285100459
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6589805549915764
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.6516956762905051
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.6667221229271868
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.5646710115576599
            name: Pearson Dot
          - type: spearman_dot
            value: 0.570198719868156
            name: Spearman Dot
          - type: pearson_max
            value: 0.6516956762905051
            name: Pearson Max
          - type: spearman_max
            value: 0.6667221229271868
            name: Spearman Max
          - type: pearson_cosine
            value: 0.6774230420538705
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6537294853166558
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.6824702119604247
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6324707043840341
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.6905615468119815
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.640725065351179
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.5834798827905125
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5962447037764929
            name: Spearman Dot
          - type: pearson_max
            value: 0.6905615468119815
            name: Pearson Max
          - type: spearman_max
            value: 0.6537294853166558
            name: Spearman Max
          - type: pearson_cosine
            value: 0.6709478850576526
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6847049462613332
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.6612883666796053
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6906896123993531
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.66070522554664
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.6880796473119815
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.609762034287328
            name: Pearson Dot
          - type: spearman_dot
            value: 0.6194587632000961
            name: Spearman Dot
          - type: pearson_max
            value: 0.6709478850576526
            name: Pearson Max
          - type: spearman_max
            value: 0.6906896123993531
            name: Spearman Max
          - type: pearson_cosine
            value: 0.5977420246846783
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.5798716781400349
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.5974348978243684
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.5952597125560467
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.5949256850264925
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.5935900431326085
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.5042542872226021
            name: Pearson Dot
          - type: spearman_dot
            value: 0.4968394689744579
            name: Spearman Dot
          - type: pearson_max
            value: 0.5977420246846783
            name: Pearson Max
          - type: spearman_max
            value: 0.5952597125560467
            name: Spearman Max
          - type: pearson_cosine
            value: 0.45623521030042163
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.44220332625465214
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.4154787596532877
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.3836945296053597
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.4111357738180186
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.3821548244303783
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.48625234725541483
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5302744622635869
            name: Spearman Dot
          - type: pearson_max
            value: 0.48625234725541483
            name: Pearson Max
          - type: spearman_max
            value: 0.5302744622635869
            name: Spearman Max
          - type: pearson_cosine
            value: 0.5929570742517215
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.6266361518449931
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.5608268850302591
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.6228972623939251
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.5579847474929831
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.6202030126844109
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.4578333834889949
            name: Pearson Dot
          - type: spearman_dot
            value: 0.5628471668594075
            name: Spearman Dot
          - type: pearson_max
            value: 0.5929570742517215
            name: Pearson Max
          - type: spearman_max
            value: 0.6266361518449931
            name: Spearman Max

SentenceTransformer based on sentence-transformers/paraphrase-multilingual-mpnet-base-v2

This is a sentence-transformers model finetuned from sentence-transformers/paraphrase-multilingual-mpnet-base-v2. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

Model Type: Sentence Transformer
Base model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
Maximum Sequence Length: 128 tokens
Output Dimensionality: 768 tokens
Similarity Function: Cosine Similarity

Model Sources

Documentation: Sentence Transformers Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("Gameselo/STS-multilingual-mpnet-base-v2")
# Run inference
sentences = [
    '一个女人正在洗澡。',
    'A woman is taking a bath.',
    'En jente børster håret sitt',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Evaluation

Metrics

Semantic Similarity

Dataset: sts-dev
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.9551
spearman_cosine	0.9593
pearson_manhattan	0.927
spearman_manhattan	0.9383
pearson_euclidean	0.9278
spearman_euclidean	0.9394
pearson_dot	0.876
spearman_dot	0.8865
pearson_max	0.9551
spearman_max	0.9593

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.948
spearman_cosine	0.9515
pearson_manhattan	0.9252
spearman_manhattan	0.9352
pearson_euclidean	0.9258
spearman_euclidean	0.9364
pearson_dot	0.8443
spearman_dot	0.8435
pearson_max	0.948
spearman_max	0.9515

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.9725
spearman_cosine	0.9766
pearson_manhattan	0.9382
spearman_manhattan	0.9487
pearson_euclidean	0.9392
spearman_euclidean	0.95
pearson_dot	0.8531
spearman_dot	0.8611
pearson_max	0.9725
spearman_max	0.9766

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.8027
spearman_cosine	0.8124
pearson_manhattan	0.7839
spearman_manhattan	0.79
pearson_euclidean	0.7836
spearman_euclidean	0.792
pearson_dot	0.7699
spearman_dot	0.782
pearson_max	0.8027
spearman_max	0.8124

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.7796
spearman_cosine	0.7703
pearson_manhattan	0.7904
spearman_manhattan	0.783
pearson_euclidean	0.7912
spearman_euclidean	0.7842
pearson_dot	0.7077
spearman_dot	0.6914
pearson_max	0.7912
spearman_max	0.7842

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.9113
spearman_cosine	0.9109
pearson_manhattan	0.897
spearman_manhattan	0.8934
pearson_euclidean	0.8986
spearman_euclidean	0.8955
pearson_dot	0.8844
spearman_dot	0.8923
pearson_max	0.9113
spearman_max	0.9109

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.9362
spearman_cosine	0.9379
pearson_manhattan	0.923
spearman_manhattan	0.9245
pearson_euclidean	0.9231
spearman_euclidean	0.9251
pearson_dot	0.907
spearman_dot	0.9186
pearson_max	0.9362
spearman_max	0.9379

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.8049
spearman_cosine	0.7987
pearson_manhattan	0.8018
spearman_manhattan	0.7828
pearson_euclidean	0.8007
spearman_euclidean	0.7825
pearson_dot	0.7895
spearman_dot	0.7819
pearson_max	0.8049
spearman_max	0.7987

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.852
spearman_cosine	0.8553
pearson_manhattan	0.8464
spearman_manhattan	0.841
pearson_euclidean	0.8468
spearman_euclidean	0.8459
pearson_dot	0.8093
spearman_dot	0.8154
pearson_max	0.852
spearman_max	0.8553

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.8752
spearman_cosine	0.8727
pearson_manhattan	0.8745
spearman_manhattan	0.8661
pearson_euclidean	0.8748
spearman_euclidean	0.8668
pearson_dot	0.8603
spearman_dot	0.852
pearson_max	0.8752
spearman_max	0.8727

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.9082
spearman_cosine	0.9068
pearson_manhattan	0.8908
spearman_manhattan	0.8852
pearson_euclidean	0.8908
spearman_euclidean	0.8851
pearson_dot	0.8889
spearman_dot	0.8966
pearson_max	0.9082
spearman_max	0.9068

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.925
spearman_cosine	0.9247
pearson_manhattan	0.9084
spearman_manhattan	0.9029
pearson_euclidean	0.9116
spearman_euclidean	0.9084
pearson_dot	0.9001
spearman_dot	0.907
pearson_max	0.925
spearman_max	0.9247

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.9133
spearman_cosine	0.9115
pearson_manhattan	0.8977
spearman_manhattan	0.8933
pearson_euclidean	0.8979
spearman_euclidean	0.8937
pearson_dot	0.8912
spearman_dot	0.8988
pearson_max	0.9133
spearman_max	0.9115

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.8985
spearman_cosine	0.8452
pearson_manhattan	0.8715
spearman_manhattan	0.8452
pearson_euclidean	0.8809
spearman_euclidean	0.8452
pearson_dot	0.8538
spearman_dot	0.8452
pearson_max	0.8985
spearman_max	0.8452

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.6495
spearman_cosine	0.6385
pearson_manhattan	0.6429
spearman_manhattan	0.6474
pearson_euclidean	0.6443
spearman_euclidean	0.6445
pearson_dot	0.6128
spearman_dot	0.6108
pearson_max	0.6495
spearman_max	0.6474

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.7441
spearman_cosine	0.7518
pearson_manhattan	0.7339
spearman_manhattan	0.7367
pearson_euclidean	0.7337
spearman_euclidean	0.7342
pearson_dot	0.6886
spearman_dot	0.6986
pearson_max	0.7441
spearman_max	0.7518

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.6279
spearman_cosine	0.6319
pearson_manhattan	0.5435
spearman_manhattan	0.6002
pearson_euclidean	0.54
spearman_euclidean	0.5955
pearson_dot	0.5658
spearman_dot	0.6069
pearson_max	0.6279
spearman_max	0.6319

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.7779
spearman_cosine	0.7876
pearson_manhattan	0.7426
spearman_manhattan	0.7789
pearson_euclidean	0.7437
spearman_euclidean	0.7806
pearson_dot	0.7214
spearman_dot	0.7489
pearson_max	0.7779
spearman_max	0.7876

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.5268
spearman_cosine	0.5774
pearson_manhattan	0.4171
spearman_manhattan	0.56
pearson_euclidean	0.4219
spearman_euclidean	0.5665
pearson_dot	0.4981
spearman_dot	0.5367
pearson_max	0.5268
spearman_max	0.5774

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.6306
spearman_cosine	0.6384
pearson_manhattan	0.6034
spearman_manhattan	0.6168
pearson_euclidean	0.6081
spearman_euclidean	0.622
pearson_dot	0.5767
spearman_dot	0.5831
pearson_max	0.6306
spearman_max	0.6384

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.5568
spearman_cosine	0.5867
pearson_manhattan	0.4924
spearman_manhattan	0.5738
pearson_euclidean	0.4906
spearman_euclidean	0.5762
pearson_dot	0.4307
spearman_dot	0.5471
pearson_max	0.5568
spearman_max	0.5867

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.5776
spearman_cosine	0.575
pearson_manhattan	0.5718
spearman_manhattan	0.5501
pearson_euclidean	0.5695
spearman_euclidean	0.5532
pearson_dot	0.5315
spearman_dot	0.5191
pearson_max	0.5776
spearman_max	0.575

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.3572
spearman_cosine	0.4336
pearson_manhattan	0.2081
spearman_manhattan	0.4355
pearson_euclidean	0.2086
spearman_euclidean	0.4402
pearson_dot	0.2234
spearman_dot	0.3707
pearson_max	0.3572
spearman_max	0.4402

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.6863
spearman_cosine	0.6621
pearson_manhattan	0.6429
spearman_manhattan	0.6484
pearson_euclidean	0.6424
spearman_euclidean	0.6486
pearson_dot	0.6352
spearman_dot	0.6159
pearson_max	0.6863
spearman_max	0.6621

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.757
spearman_cosine	0.7511
pearson_manhattan	0.7191
spearman_manhattan	0.714
pearson_euclidean	0.7204
spearman_euclidean	0.7258
pearson_dot	0.7144
spearman_dot	0.7284
pearson_max	0.757
spearman_max	0.7511

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.6503
spearman_cosine	0.6625
pearson_manhattan	0.6474
spearman_manhattan	0.659
pearson_euclidean	0.6517
spearman_euclidean	0.6667
pearson_dot	0.5647
spearman_dot	0.5702
pearson_max	0.6517
spearman_max	0.6667

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.6774
spearman_cosine	0.6537
pearson_manhattan	0.6825
spearman_manhattan	0.6325
pearson_euclidean	0.6906
spearman_euclidean	0.6407
pearson_dot	0.5835
spearman_dot	0.5962
pearson_max	0.6906
spearman_max	0.6537

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.6709
spearman_cosine	0.6847
pearson_manhattan	0.6613
spearman_manhattan	0.6907
pearson_euclidean	0.6607
spearman_euclidean	0.6881
pearson_dot	0.6098
spearman_dot	0.6195
pearson_max	0.6709
spearman_max	0.6907

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.5977
spearman_cosine	0.5799
pearson_manhattan	0.5974
spearman_manhattan	0.5953
pearson_euclidean	0.5949
spearman_euclidean	0.5936
pearson_dot	0.5043
spearman_dot	0.4968
pearson_max	0.5977
spearman_max	0.5953

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.4562
spearman_cosine	0.4422
pearson_manhattan	0.4155
spearman_manhattan	0.3837
pearson_euclidean	0.4111
spearman_euclidean	0.3822
pearson_dot	0.4863
spearman_dot	0.5303
pearson_max	0.4863
spearman_max	0.5303

Semantic Similarity

Dataset: sts-test
Evaluated with EmbeddingSimilarityEvaluator

Metric	Value
pearson_cosine	0.593
spearman_cosine	0.6266
pearson_manhattan	0.5608
spearman_manhattan	0.6229
pearson_euclidean	0.558
spearman_euclidean	0.6202
pearson_dot	0.4578
spearman_dot	0.5628
pearson_max	0.593
spearman_max	0.6266

Training Details

Training Dataset

Unnamed Dataset

Size: 226,547 training samples
Columns: sentence_0, sentence_1, and label
Approximate statistics based on the first 1000 samples:
sentence_0 sentence_1 label
type string string float
details
min: 3 tokens
mean: 20.05 tokens
max: 128 tokens

min: 4 tokens
mean: 19.94 tokens
max: 128 tokens

min: 0.0
mean: 1.92
max: 398.6

	sentence_0	sentence_1	label
type	string	string	float
details	min: 3 tokens mean: 20.05 tokens max: 128 tokens	min: 4 tokens mean: 19.94 tokens max: 128 tokens	min: 0.0 mean: 1.92 max: 398.6

Samples:

sentence_0	sentence_1	label
`Bir kadın makineye dikiş dikiyor.`	`Bir kadın biraz et ekiyor.`	`0.12`
`Snowden 'gegeven vluchtelingendocument door Ecuador'.`	`Snowden staat op het punt om uit Moskou te vliegen`	`0.24000000953674316`
`Czarny pies idzie mostem przez wodę`	`Czarny pies nie idzie mostem przez wodę`	`0.74000000954`

Loss: AnglELoss with these parameters:

{
    "scale": 20.0,
    "similarity_fct": "pairwise_angle_sim"
}

Training Hyperparameters

Non-Default Hyperparameters

per_device_train_batch_size: 256
per_device_eval_batch_size: 256
num_train_epochs: 10
multi_dataset_batch_sampler: round_robin

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
prediction_loss_only: True
per_device_train_batch_size: 256
per_device_eval_batch_size: 256
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
learning_rate: 5e-05
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1
num_train_epochs: 10
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.0
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 42
data_seed: None
jit_mode_eval: False
use_ipex: False
bf16: False
fp16: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: False
dataloader_num_workers: 0
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: False
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'gradient_accumulation_kwargs': None}
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
ddp_find_unused_parameters: None
ddp_bucket_cap_mb: None
ddp_broadcast_buffers: False
dataloader_pin_memory: True
dataloader_persistent_workers: False
skip_memory_metrics: True
use_legacy_prediction_loop: False
push_to_hub: False
resume_from_checkpoint: None
hub_model_id: None
hub_strategy: every_save
hub_private_repo: False
hub_always_push: False
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
eval_do_concat_batches: True
fp16_backend: auto
push_to_hub_model_id: None
push_to_hub_organization: None
mp_parameters:
auto_find_batch_size: False
full_determinism: False
torchdynamo: None
ray_scope: last
ddp_timeout: 1800
torch_compile: False
torch_compile_backend: None
torch_compile_mode: None
dispatch_batches: None
split_batches: None
include_tokens_per_second: False
include_num_input_tokens_seen: False
neftune_noise_alpha: None
optim_target_modules: None
batch_sampler: batch_sampler
multi_dataset_batch_sampler: round_robin

Training Logs

Epoch	Step	Training Loss	sts-dev_spearman_cosine	sts-test_spearman_cosine
0.5650	500	10.9426	-	-
1.0	885	-	0.9202	-
1.1299	1000	9.7184	-	-
1.6949	1500	9.5348	-	-
2.0	1770	-	0.9400	-
2.2599	2000	9.4412	-	-
2.8249	2500	9.3097	-	-
3.0	2655	-	0.9489	-
3.3898	3000	9.2357	-	-
3.9548	3500	9.1594	-	-
4.0	3540	-	0.9528	-
4.5198	4000	9.0963	-	-
5.0	4425	-	0.9553	-
5.0847	4500	9.0382	-	-
5.6497	5000	8.9837	-	-
6.0	5310	-	0.9567	-
6.2147	5500	8.9403	-	-
6.7797	6000	8.8841	-	-
7.0	6195	-	0.9581	-
7.3446	6500	8.8513	-	-
7.9096	7000	8.81	-	-
8.0	7080	-	0.9582	-
8.4746	7500	8.8069	-	-
9.0	7965	-	0.9589	-
9.0395	8000	8.7616	-	-
9.6045	8500	8.7521	-	-
10.0	8850	-	0.9593	0.6266

Framework Versions

Python: 3.9.7
Sentence Transformers: 3.0.0
Transformers: 4.40.1
PyTorch: 2.3.0+cu121
Accelerate: 0.29.3
Datasets: 2.19.0
Tokenizers: 0.19.1

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

AnglELoss

@misc{li2023angleoptimized,
    title={AnglE-optimized Text Embeddings}, 
    author={Xianming Li and Jing Li},
    year={2023},
    eprint={2309.12871},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}