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
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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
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value: 0.6159110999161411
name: Spearman Dot
- type: pearson_max
value: 0.6863427356006826
name: Pearson Max
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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
/!\ This model achieves SOTA results in the MTEB STS multilingual Leaderboard (in "other"). Here is the comparison
State-of-the-art results (Multi) STSb-XLM-RoBERTa-base Paraphrase Multilingual MPNet base v2
Average 73.17 71.68 73.89 STS17 (ar-ar) 81.87 80.43 81.24 STS17 (en-ar) 81.22 76.3 77.03 STS17 (en-de) 87.3 91.06 91.09 STS17 (en-tr) 77.18 80.74 79.87 STS17 (es-en) 88.24 83.09 85.53 STS17 (es-es) 88.25 84.16 87.27 STS17 (fr-en) 88.06 91.33 90.68 STS17 (it-en) 89.68 92.87 92.47 STS17 (ko-ko) 83.69 97.67 97.66 STS17 (nl-en) 88.25 92.13 91.15 STS22 (ar) 58.67 58.67 62.66 STS22 (de) 60.12 52.17 57.74 STS22 (de-en) 60.92 58.5 57.5 STS22 (de-fr) 67.79 51.28 57.99 STS22 (de-pl) 58.69 44.56 44.22 STS22 (es) 68.57 63.68 66.21 STS22 (es-en) 78.8 70.65 75.18 STS22 (es-it) 75.04 60.88 66.25 STS22 (fr) 83.75 76.46 78.76 STS22 (fr-pl) 84.52 84.52 84.52 STS22 (it) 79.28 66.73 68.47 STS22 (pl) 42.08 41.18 43.36 STS22 (pl-en) 77.5 64.35 75.11 STS22 (ru) 61.71 58.59 58.67 STS22 (tr) 68.72 57.52 63.84 STS22 (zh-en) 71.88 60.69 65.37 STSb 89.86 95.05 95.15
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 |
Evalutation results vs SOTA results
- 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 |
Training Details
Training Dataset
Unnamed Dataset
- Size: 226,547 training samples
- Columns:
sentence_0
,sentence_1
, andlabel
- 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
- 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
: 256per_device_eval_batch_size
: 256num_train_epochs
: 10multi_dataset_batch_sampler
: round_robin
All Hyperparameters
Click to expand
overwrite_output_dir
: Falsedo_predict
: Falseprediction_loss_only
: Trueper_device_train_batch_size
: 256per_device_eval_batch_size
: 256per_gpu_train_batch_size
: Noneper_gpu_eval_batch_size
: Nonegradient_accumulation_steps
: 1eval_accumulation_steps
: Nonelearning_rate
: 5e-05weight_decay
: 0.0adam_beta1
: 0.9adam_beta2
: 0.999adam_epsilon
: 1e-08max_grad_norm
: 1num_train_epochs
: 10max_steps
: -1lr_scheduler_type
: linearlr_scheduler_kwargs
: {}warmup_ratio
: 0.0warmup_steps
: 0log_level
: passivelog_level_replica
: warninglog_on_each_node
: Truelogging_nan_inf_filter
: Truesave_safetensors
: Truesave_on_each_node
: Falsesave_only_model
: Falseno_cuda
: Falseuse_cpu
: Falseuse_mps_device
: Falseseed
: 42data_seed
: Nonejit_mode_eval
: Falseuse_ipex
: Falsebf16
: Falsefp16
: Falsefp16_opt_level
: O1half_precision_backend
: autobf16_full_eval
: Falsefp16_full_eval
: Falsetf32
: Nonelocal_rank
: 0ddp_backend
: Nonetpu_num_cores
: Nonetpu_metrics_debug
: Falsedebug
: []dataloader_drop_last
: Falsedataloader_num_workers
: 0dataloader_prefetch_factor
: Nonepast_index
: -1disable_tqdm
: Falseremove_unused_columns
: Truelabel_names
: Noneload_best_model_at_end
: Falseignore_data_skip
: Falsefsdp
: []fsdp_min_num_params
: 0fsdp_config
: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap
: Noneaccelerator_config
: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'gradient_accumulation_kwargs': None}deepspeed
: Nonelabel_smoothing_factor
: 0.0optim
: adamw_torchoptim_args
: Noneadafactor
: Falsegroup_by_length
: Falselength_column_name
: lengthddp_find_unused_parameters
: Noneddp_bucket_cap_mb
: Noneddp_broadcast_buffers
: Falsedataloader_pin_memory
: Truedataloader_persistent_workers
: Falseskip_memory_metrics
: Trueuse_legacy_prediction_loop
: Falsepush_to_hub
: Falseresume_from_checkpoint
: Nonehub_model_id
: Nonehub_strategy
: every_savehub_private_repo
: Falsehub_always_push
: Falsegradient_checkpointing
: Falsegradient_checkpointing_kwargs
: Noneinclude_inputs_for_metrics
: Falseeval_do_concat_batches
: Truefp16_backend
: autopush_to_hub_model_id
: Nonepush_to_hub_organization
: Nonemp_parameters
:auto_find_batch_size
: Falsefull_determinism
: Falsetorchdynamo
: Noneray_scope
: lastddp_timeout
: 1800torch_compile
: Falsetorch_compile_backend
: Nonetorch_compile_mode
: Nonedispatch_batches
: Nonesplit_batches
: Noneinclude_tokens_per_second
: Falseinclude_num_input_tokens_seen
: Falseneftune_noise_alpha
: Noneoptim_target_modules
: Nonebatch_sampler
: batch_samplermulti_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}
}