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avsolatorio/all-MiniLM-L6-v2-MEDI-MTEB-triplet-randproj-64-final

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face

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all-MiniLM-L6-v2 trained on MEDI-MTEB triplets

This is a sentence-transformers model finetuned from sentence-transformers/all-MiniLM-L6-v2 on the NQ, pubmed, spectertraintriples, S2ORCcitationsabstracts, fever, gooaqpairs, codesearchnet, wikihow, WikiAnswers, eli5questionanswer, amazon-qa, medmcqa, zeroshot, TriviaQApairs, PAQpairs, stackexchangeduplicatequestionstitle-bodytitle-body, trex, flickr30kcaptions, hotpotqa, task671ambigqatextgeneration, task061ropesanswergeneration, task285imdbanswergeneration, task905hatespeechoffensiveclassification, task566circaclassification, task184snlientailmenttoneutraltextmodification, task280stereosetclassificationstereotypetype, task1599smcalflowclassification, task1384dealornodialogclassification, task591sciqanswergeneration, task823peixian-rtgendersentimentanalysis, task023cosmosqaquestiongeneration, task900freebaseqacategoryclassification, task924event2mindwordgeneration, task152tomqafindlocationeasynoise, task1368healthfactsentencegeneration, task1661superglueclassification, task1187politifactclassification, task1728webnlgdatatotext, task112assetsimplesentenceidentification, task1340msrtextcompressioncompression, task072abductivenlianswergeneration, task1504hatexplainanswergeneration, task684onlineprivacypolicytextinformationtypegeneration, task1290xsumsummarization, task075squad1.1answergeneration, task1587scifactclassification, task384socialiqaquestionclassification, task1555scitailanswergeneration, task1532dailydialogemotionclassification, task239tweetqaanswergeneration, task596mochaquestiongeneration, task1411dartsubjectidentification, task1359numersenseanswergeneration, task329gapclassification, task220rocstoriestitleclassification, task316crows-pairsclassificationstereotype, task495semevalheadlineclassification, task1168browncoarsepostagging, task348squad2.0unanswerablequestiongeneration, task049multircquestionsneededtoanswer, task1534dailydialogquestionclassification, task322jigsawclassificationthreat, task295semeval2020task4commonsensereasoning, task186snlicontradictiontoentailmenttextmodification, task034winograndequestionmodificationobject, task160replaceletterinasentence, task469mrqaanswergeneration, task105storycloze-rocstoriessentencegeneration, task649raceblankquestiongeneration, task1536dailydialoghappinessclassification, task683onlineprivacypolicytextpurposeanswergeneration, task024cosmosqaanswergeneration, task584udepsengfinepostagging, task066timetravelbinaryconsistencyclassification, task413mickeyensentenceperturbationgeneration, task182duorcquestiongeneration, task028dropanswergeneration, task1601webquestionsanswergeneration, task1295adversarialqaquestionanswering, task201mnlineutralclassification, task038qasccombinedfact, task293storycommonsenseemotiontextgeneration, task572recipenlgtextgeneration, task517emoclassifyemotionofdialogue, task382hybridqaanswergeneration, task176breakdecomposequestions, task1291multinewssummarization, task155countnounsverbs, task031winograndequestiongenerationobject, task279stereosetclassificationstereotype, task1336peixianequityevaluationcorpusgenderclassifier, task508scruplesdilemmasmoreethicalisidentifiable, task518emodifferentdialogueemotions, task077splashexplanationtosql, task923event2mindclassifier, task470mrqaquestiongeneration, task638multiwozclassification, task1412webquestionsquestionanswering, task847pubmedqaquestiongeneration, task678ollieactualrelationshipanswergeneration, task290tellmewhyquestionanswerability, task575airdialogueclassification, task189snlineutraltocontradictiontextmodification, task026dropquestiongeneration, task162countwordsstartingwithletter, task079conalaconcatstrings, task610conllppner, task046miscellaneousquestiontyping, task197mnlidomainanswergeneration, task1325qazrequestiongenerationonsubjectrelation, task430sentevalsubjectcount, task672nummersense, task402grailqaparaphrasegeneration, task904hatespeechoffensiveclassification, task192hotpotqasentencegeneration, task069abductivenliclassification, task574airdialoguesentencegeneration, task187snlientailmenttocontradictiontextmodification, task749glucosereversecauseemotiondetection, task1552scitailquestiongeneration, task750aquamultiplechoiceanswering, task327jigsawclassificationtoxic, task1502hatexplainclassification, task328jigsawclassificationinsult, task304numericfusedheadresolution, task1293kilttaskshotpotqaquestionanswering, task216rocstoriescorrectanswergeneration, task1326qazrequestiongenerationfromanswer, task1338peixianequityevaluationcorpussentimentclassifier, task1729personachatgeneratenext, task1202atomicclassificationxneed, task400pawsparaphraseclassification, task502scruplesanecdoteswhoiswrongverification, task088identifytypoverification, task221rocstoriestwochoiceclassification, task200mnlientailmentclassification, task074squad1.1questiongeneration, task581socialiqaquestiongeneration, task1186nnehrngoclassification, task898freebaseqaanswergeneration, task1408dartsimilarityclassification, task168strategyqaquestiondecomposition, task1357xlsumsummarygeneration, task390torquetextspanselection, task165mcscriptquestionansweringcommonsense, task1533dailydialogformalclassification, task002quorefanswergeneration, task1297qascquestionanswering, task305jeopardyanswergenerationnormal, task029winograndefullobject, task1327qazreanswergenerationfromquestion, task326jigsawclassificationobscene, task1542everyithelementfromstarting, task570recipenlgnergeneration, task1409darttextgeneration, task401numericfusedheadreference, task846pubmedqaclassification, task1712pokiclassification, task344hybridqaanswergeneration, task875emotionclassification, task1214atomicclassificationxwant, task106scruplesethicaljudgment, task238iircanswerfrompassageanswergeneration, task1391winograndeeasyanswergeneration, task195sentiment140classification, task163countwordsendingwithletter, task579socialiqaclassification, task569recipenlgtextgeneration, task1602webquestionquestiongenreation, task747glucosecauseemotiondetection, task219rocstoriestitleanswergeneration, task178quartzquestionanswering, task103facts2storylongtextgeneration, task301recordquestiongeneration, task1369healthfactsentencegeneration, task515sentevaloddwordout, task496semevalanswergeneration, task1658billsumsummarization, task1204atomicclassificationhinderedby, task1392supergluemultircanswerverification, task306jeopardyanswergenerationdouble, task1286openbookqaquestionanswering, task159checkfrequencyofwordsinsentencepair, task151tomqafindlocationeasyclean, task323jigsawclassificationsexuallyexplicit, task037qascgeneraterelatedfact, task027dropanswertypegeneration, task1596event2mindtextgeneration2, task141odd-man-outclassificationcategory, task194duorcanswergeneration, task679hopeedienglishtextclassification, task246dreamquestiongeneration, task1195disflqadisfluenttofluentconversion, task065timetravelconsistentsentenceclassification, task351winomtclassificationgenderidentifiabilityanti, task580socialiqaanswergeneration, task583udepsengcoarsepostagging, task202mnlicontradictionclassification, task222rocstoriestwochioceslottingclassification, task498scruplesanecdoteswhoiswrongclassification, task067abductivenlianswergeneration, task616colaclassification, task286olidoffensejudgment, task188snlineutraltoentailmenttextmodification, task223quartzexplanationgeneration, task820protoqaanswergeneration, task196sentiment140answergeneration, task1678mathqaanswerselection, task349squad2.0answerableunanswerablequestionclassification, task154tomqafindlocationhardnoise, task333hateevalclassificationhateen, task235iircquestionfromsubtextanswergeneration, task1554scitailclassification, task210logic2textstructuredtextgeneration, task035winograndequestionmodificationperson, task230iircpassageclassification, task1356xlsumtitlegeneration, task1726mathqacorrectanswergeneration, task302recordclassification, task380boolqyesnoquestion, task212logic2textclassification, task748glucosereversecauseeventdetection, task834mathdatasetclassification, task350winomtclassificationgenderidentifiabilitypro, task191hotpotqaquestiongeneration, task236iircquestionfrompassageanswergeneration, task217rocstoriesorderinganswergeneration, task568circaquestiongeneration, task614glucosecauseeventdetection, task361spolinyesandpromptresponseclassification, task421persentsentencesentimentclassification, task203mnlisentencegeneration, task420persentdocumentsentimentclassification, task153tomqafindlocationhardclean, task346hybridqaclassification, task1211atomicclassificationhassubevent, task360spolinyesandresponsegeneration, task510reddittifutitlesummarization, task511reddittifulongtextsummarization, task345hybridqaanswergeneration, task270csrgcounterfactualcontextgeneration, task307jeopardyanswergenerationfinal, task001quorefquestiongeneration, task089swapwordsverification, task1196atomicclassificationoeffect, task080piqaanswergeneration, task1598nyclongtextgeneration, task240tweetqaquestiongeneration, task615moviesqaanswergeneration, task1347gluests-bsimilarityclassification, task114isthegivenwordlongest, task292storycommonsensecharactertextgeneration, task115helpadviceclassification, task431sentevalobjectcount, task1360numersensemultiplechoiceqageneration, task177para-nmtparaphrasing, task132daistextmodification, task269csrgcounterfactualstorygeneration, task233iirclinkexistsclassification, task161countwordscontainingletter, task1205atomicclassificationisafter, task571recipenlgnergeneration, task1292yelpreviewfulltextcategorization, task428sentevalinversion, task311racequestiongeneration, task429sentevaltense, task403creakcommonsenseinference, task929productsreviewsclassification, task582naturalquestionanswergeneration, task237iircanswerfromsubtextanswergeneration, task050multircanswerability, task184breakgeneratequestion, task669ambigqaanswergeneration, task169strategyqasentencegeneration, task500scruplesanecdotestitlegeneration, task241tweetqaclassification, task1345glueqqpquestionparaprashing, task218rocstoriesswaporderanswergeneration, task613politifacttextgeneration, task1167penntreebankcoarsepostagging, task1422mathqaphysics, task247dreamanswergeneration, task199mnliclassification, task164mcscriptquestionansweringtext, task1541agnewsclassification, task516sentevalconjointsinversion, task294storycommonsensemotivtextgeneration, task501scruplesanecdotesposttypeverification, task213rocstoriescorrectendingclassification, task821protoqaquestiongeneration, task493reviewpolarityclassification, task308jeopardyanswergenerationall, task1595event2mindtextgeneration1, task040qascquestiongeneration, task231iirclinkclassification, task1727wiqawhatistheeffect, task578curiositydialogsanswergeneration, task310raceclassification, task309raceanswergeneration, task379agnewstopicclassification, task030winograndefullperson, task1540parsedpdfssummarization, task039qascfindoverlappingwords, task1206atomicclassificationisbefore, task157countvowelsandconsonants, task339recordanswergeneration, task453swaganswergeneration, task848pubmedqaclassification, task673googlewellformedqueryclassification, task676ollierelationshipanswergeneration, task268caseholdlegalanswergeneration, task844financialphrasebankclassification, task330gapanswergeneration, task595mochaanswergeneration, task1285kpakeypointmatching, task234iircpassagelineanswergeneration, task494reviewpolarityanswergeneration, task670ambigqaquestiongeneration, task289gigawordsummarization, npr, nli, SimpleWiki, amazonreview2018, ccnewstitletext, agnews, xsum, msmarco, yahooanswerstitleanswer, squadpairs, wow, mteb-amazoncounterfactual-avstriplets, mteb-amazonmassiveintent-avstriplets, mteb-amazonmassivescenario-avstriplets, mteb-amazonreviewsmulti-avstriplets, mteb-banking77-avstriplets, mteb-emotion-avstriplets, mteb-imdb-avstriplets, mteb-mtopdomain-avstriplets, mteb-mtopintent-avstriplets, mteb-toxicconversations50k-avstriplets, mteb-tweetsentimentextraction-avstriplets and covid-bing-query-gpt4-avs_triplets datasets. 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/all-MiniLM-L6-v2
—Maximum Sequence Length: 256 tokens
—Output Dimensionality: 768 dimensions
—Similarity Function: Cosine Similarity
—Training Datasets:
—NQ
—pubmed
—spectertraintriples
—S2ORCcitationsabstracts
—fever
—gooaq_pairs
—codesearchnet
—wikihow
—WikiAnswers
—eli5questionanswer
—amazon-qa
—medmcqa
—zeroshot
—TriviaQA_pairs
—PAQ_pairs
—stackexchangeduplicatequestionstitle-bodytitle-body
—trex
—flickr30k_captions
—hotpotqa
—task671ambigqatext_generation
—task061ropesanswer_generation
—task285imdbanswer_generation
—task905hatespeechoffensiveclassification
—task566circaclassification
—task184snlientailmenttoneutraltextmodification
—task280stereosetclassificationstereotypetype
—task1599smcalflowclassification
—task1384dealornodialog_classification
—task591sciqanswer_generation
—task823peixian-rtgendersentiment_analysis
—task023cosmosqaquestion_generation
—task900freebaseqacategoryclassification
—task924event2mindword_generation
—task152tomqafindlocationeasy_noise
—task1368healthfactsentence_generation
—task1661superglue_classification
—task1187politifactclassification
—task1728webnlgdatato_text
—task112assetsimplesentenceidentification
—task1340msrtextcompressioncompression
—task072abductivenlianswer_generation
—task1504hatexplainanswer_generation
—task684onlineprivacypolicytextinformationtype_generation
—task1290xsumsummarization
—task075squad1.1answer_generation
—task1587scifactclassification
—task384socialiqaquestion_classification
—task1555scitailanswer_generation
—task1532dailydialogemotionclassification
—task239tweetqaanswer_generation
—task596mochaquestion_generation
—task1411dartsubject_identification
—task1359numersenseanswergeneration
—task329gapclassification
—task220rocstoriestitle_classification
—task316crows-pairsclassification_stereotype
—task495semevalheadline_classification
—task1168browncoarsepostagging
—task348squad2.0unanswerablequestiongeneration
—task049multircquestionsneededto_answer
—task1534dailydialogquestionclassification
—task322jigsawclassification_threat
—task295semeval2020task4commonsense_reasoning
—task186snlicontradictiontoentailmenttextmodification
—task034winograndequestionmodificationobject
—task160replaceletterina_sentence
—task469mrqaanswer_generation
—task105storycloze-rocstoriessentencegeneration
—task649raceblankquestiongeneration
—task1536dailydialoghappinessclassification
—task683onlineprivacypolicytextpurposeanswer_generation
—task024cosmosqaanswer_generation
—task584udepsengfinepos_tagging
—task066timetravelbinaryconsistencyclassification
—task413mickeyensentenceperturbation_generation
—task182duorcquestion_generation
—task028dropanswer_generation
—task1601webquestionsanswer_generation
—task1295adversarialqaquestionanswering
—task201mnlineutral_classification
—task038qasccombined_fact
—task293storycommonsenseemotiontextgeneration
—task572recipenlgtextgeneration
—task517emoclassifyemotionof_dialogue
—task382hybridqaanswer_generation
—task176breakdecompose_questions
—task1291multinews_summarization
—task155countnouns_verbs
—task031winograndequestiongenerationobject
—task279stereosetclassification_stereotype
—task1336peixianequityevaluationcorpusgenderclassifier
—task508scruplesdilemmasmoreethical_isidentifiable
—task518emodifferentdialogueemotions
—task077splashexplanationtosql
—task923event2mindclassifier
—task470mrqaquestion_generation
—task638multiwoz_classification
—task1412webquestionsquestionanswering
—task847pubmedqaquestion_generation
—task678ollieactualrelationshipanswer_generation
—task290tellmewhyquestion_answerability
—task575airdialogue_classification
—task189snlineutraltocontradictiontextmodification
—task026dropquestion_generation
—task162countwordsstartingwith_letter
—task079conalaconcat_strings
—task610conllppner
—task046miscellaneousquestion_typing
—task197mnlidomainanswergeneration
—task1325qazrequestiongenerationonsubject_relation
—task430sentevalsubject_count
—task672_nummersense
—task402grailqaparaphrase_generation
—task904hatespeechoffensiveclassification
—task192hotpotqasentence_generation
—task069abductivenliclassification
—task574airdialoguesentencegeneration
—task187snlientailmenttocontradictiontextmodification
—task749glucosereversecauseemotion_detection
—task1552scitailquestion_generation
—task750aquamultiplechoiceanswering
—task327jigsawclassification_toxic
—task1502hatexplainclassification
—task328jigsawclassification_insult
—task304numericfusedheadresolution
—task1293kilttaskshotpotqaquestion_answering
—task216rocstoriescorrectanswergeneration
—task1326qazrequestiongenerationfromanswer
—task1338peixianequityevaluationcorpussentimentclassifier
—task1729personachatgenerate_next
—task1202atomicclassification_xneed
—task400pawsparaphrase_classification
—task502scruplesanecdoteswhoiswrongverification
—task088identifytypo_verification
—task221rocstoriestwochoiceclassification
—task200mnlientailment_classification
—task074squad1.1question_generation
—task581socialiqaquestion_generation
—task1186nnehrngo_classification
—task898freebaseqaanswergeneration
—task1408dartsimilarity_classification
—task168strategyqaquestion_decomposition
—task1357xlsumsummary_generation
—task390torquetextspanselection
—task165mcscriptquestionansweringcommonsense
—task1533dailydialogformalclassification
—task002quorefanswer_generation
—task1297qascquestion_answering
—task305jeopardyanswergenerationnormal
—task029winograndefull_object
—task1327qazreanswergenerationfromquestion
—task326jigsawclassification_obscene
—task1542everyithelementfrom_starting
—task570recipenlgnergeneration
—task1409darttext_generation
—task401numericfusedheadreference
—task846pubmedqaclassification
—task1712pokiclassification
—task344hybridqaanswer_generation
—task875emotionclassification
—task1214atomicclassification_xwant
—task106scruplesethical_judgment
—task238iircanswerfrompassageanswergeneration
—task1391winograndeeasyanswergeneration
—task195sentiment140classification
—task163countwordsendingwith_letter
—task579socialiqaclassification
—task569recipenlgtextgeneration
—task1602webquestionquestion_genreation
—task747glucosecauseemotiondetection
—task219rocstoriestitleanswergeneration
—task178quartzquestion_answering
—task103facts2storylongtextgeneration
—task301recordquestion_generation
—task1369healthfactsentence_generation
—task515sentevaloddwordout
—task496semevalanswer_generation
—task1658billsumsummarization
—task1204atomicclassification_hinderedby
—task1392supergluemultircanswerverification
—task306jeopardyanswergenerationdouble
—task1286openbookqaquestion_answering
—task159checkfrequencyofwordsinsentence_pair
—task151tomqafindlocationeasy_clean
—task323jigsawclassificationsexuallyexplicit
—task037qascgeneraterelatedfact
—task027dropanswertypegeneration
—task1596event2mindtextgeneration2
—task141odd-man-outclassification_category
—task194duorcanswer_generation
—task679hopeedienglishtext_classification
—task246dreamquestion_generation
—task1195disflqadisfluenttofluent_conversion
—task065timetravelconsistentsentenceclassification
—task351winomtclassificationgenderidentifiability_anti
—task580socialiqaanswer_generation
—task583udepsengcoarsepos_tagging
—task202mnlicontradiction_classification
—task222rocstoriestwochioceslotting_classification
—task498scruplesanecdoteswhoiswrongclassification
—task067abductivenlianswer_generation
—task616colaclassification
—task286olidoffense_judgment
—task188snlineutraltoentailmenttextmodification
—task223quartzexplanation_generation
—task820protoqaanswer_generation
—task196sentiment140answer_generation
—task1678mathqaanswer_selection
—task349squad2.0answerableunanswerablequestion_classification
—task154tomqafindlocationhard_noise
—task333hateevalclassificationhateen
—task235iircquestionfromsubtextanswergeneration
—task1554scitailclassification
—task210logic2textstructuredtextgeneration
—task035winograndequestionmodificationperson
—task230iircpassage_classification
—task1356xlsumtitle_generation
—task1726mathqacorrectanswergeneration
—task302recordclassification
—task380boolqyesnoquestion
—task212logic2textclassification
—task748glucosereversecauseevent_detection
—task834mathdatasetclassification
—task350winomtclassificationgenderidentifiability_pro
—task191hotpotqaquestion_generation
—task236iircquestionfrompassageanswergeneration
—task217rocstoriesorderinganswergeneration
—task568circaquestion_generation
—task614glucosecauseeventdetection
—task361spolinyesandpromptresponse_classification
—task421persentsentencesentimentclassification
—task203mnlisentence_generation
—task420persentdocumentsentimentclassification
—task153tomqafindlocationhard_clean
—task346hybridqaclassification
—task1211atomicclassification_hassubevent
—task360spolinyesandresponsegeneration
—task510reddittifutitlesummarization
—task511reddittifulongtext_summarization
—task345hybridqaanswer_generation
—task270csrgcounterfactualcontextgeneration
—task307jeopardyanswergenerationfinal
—task001quorefquestion_generation
—task089swapwords_verification
—task1196atomicclassification_oeffect
—task080piqaanswer_generation
—task1598nyclongtextgeneration
—task240tweetqaquestion_generation
—task615moviesqaanswer_generation
—task1347gluests-bsimilarityclassification
—task114isthegivenword_longest
—task292storycommonsensecharactertextgeneration
—task115helpadvice_classification
—task431sentevalobject_count
—task1360numersensemultiplechoiceqageneration
—task177para-nmtparaphrasing
—task132daistext_modification
—task269csrgcounterfactualstorygeneration
—task233iirclinkexistsclassification
—task161countwordscontainingletter
—task1205atomicclassification_isafter
—task571recipenlgnergeneration
—task1292yelpreviewfulltext_categorization
—task428sentevalinversion
—task311racequestion_generation
—task429sentevaltense
—task403creakcommonsense_inference
—task929productsreviews_classification
—task582naturalquestionanswer_generation
—task237iircanswerfromsubtextanswergeneration
—task050multircanswerability
—task184breakgenerate_question
—task669ambigqaanswer_generation
—task169strategyqasentence_generation
—task500scruplesanecdotestitlegeneration
—task241tweetqaclassification
—task1345glueqqpquestionparaprashing
—task218rocstoriesswaporderanswer_generation
—task613politifacttext_generation
—task1167penntreebankcoarsepos_tagging
—task1422mathqaphysics
—task247dreamanswer_generation
—task199mnliclassification
—task164mcscriptquestionansweringtext
—task1541agnewsclassification
—task516sentevalconjoints_inversion
—task294storycommonsensemotivtextgeneration
—task501scruplesanecdotesposttype_verification
—task213rocstoriescorrectendingclassification
—task821protoqaquestion_generation
—task493reviewpolarity_classification
—task308jeopardyanswergenerationall
—task1595event2mindtextgeneration1
—task040qascquestion_generation
—task231iirclink_classification
—task1727wiqawhatisthe_effect
—task578curiositydialogsanswergeneration
—task310raceclassification
—task309raceanswer_generation
—task379agnewstopic_classification
—task030winograndefull_person
—task1540parsedpdfs_summarization
—task039qascfindoverlappingwords
—task1206atomicclassification_isbefore
—task157countvowelsandconsonants
—task339recordanswer_generation
—task453swaganswer_generation
—task848pubmedqaclassification
—task673googlewellformedqueryclassification
—task676ollierelationshipanswergeneration
—task268caseholdlegalanswergeneration
—task844financialphrasebank_classification
—task330gapanswer_generation
—task595mochaanswer_generation
—task1285kpakeypoint_matching
—task234iircpassagelineanswer_generation
—task494reviewpolarityanswergeneration
—task670ambigqaquestion_generation
—task289gigawordsummarization
—npr
—nli
—SimpleWiki
—amazonreview2018
—ccnewstitletext
—agnews
—xsum
—msmarco
—yahooanswerstitle_answer
—squad_pairs
—wow
—mteb-amazoncounterfactual-avstriplets
—mteb-amazonmassiveintent-avs_triplets
—mteb-amazonmassivescenario-avs_triplets
—mteb-amazonreviewsmulti-avs_triplets
—mteb-banking77-avs_triplets
—mteb-emotion-avs_triplets
—mteb-imdb-avs_triplets
—mteb-mtopdomain-avstriplets
—mteb-mtopintent-avstriplets
—mteb-toxicconversations50k-avs_triplets
—mteb-tweetsentimentextraction-avs_triplets
—covid-bing-query-gpt4-avs_triplets
—Language: en
—License: apache-2.0

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': 256, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): RandomProjection({'in_features': 384, 'out_features': 768, 'seed': 42})
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

bash

pip install -U sentence-transformers

Then you can load this model and run inference.

python

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("avsolatorio/all-MiniLM-L6-v2-MEDI-MTEB-triplet-randproj-64-final")
# Run inference
sentences = [
    'Does early second-trimester sonography predict adverse perinatal outcomes in monochorionic diamniotic twin pregnancies?',
    'To determine whether intertwin discordant abdominal circumference, femur length, head circumference, and estimated fetal weight sonographic measurements in early second-trimester monochorionic diamniotic twins predict adverse obstetric and neonatal outcomes.We conducted a multicenter retrospective cohort study involving 9 regional perinatal centers in the United States. We examined the records of all monochorionic diamniotic twin pregnancies with two live fetuses at the 16- to 18-week sonographic examination who had serial follow-up sonography until delivery. The intertwin discordance in abdominal circumference, femur length, head circumference, and estimated fetal weight was calculated as the difference between the two fetuses, expressed as a percentage of the larger using the 16- to 18-week sonographic measurements. An adverse composite obstetric outcome was defined as the occurrence of 1 or more of the following in either fetus: intrauterine growth restriction, twin-twin transfusion syndrome, intrauterine fetal death, abnormal growth discordance (≥20% difference), and very preterm birth at or before 28 weeks. An adverse composite neonatal outcome was defined as the occurrence of 1 or more of the following: respiratory distress syndrome, any stage of intraventricular hemorrhage, 5-minute Apgar score less than 7, necrotizing enterocolitis, culture-proven early-onset sepsis, and neonatal death. Receiver operating characteristic and logistic regression-with-generalized estimating equation analyses were constructed.Among the 177 monochorionic diamniotic twin pregnancies analyzed, intertwin abdominal circumference and estimated fetal weight discordances were only predictive of adverse composite obstetric outcomes (areas under the curve, 79% and 80%, respectively). Receiver operating characteristic curves showed that intertwin discordances in abdominal circumference, femur length, head circumference, and estimated fetal weight were not acceptable predictors of twin-twin transfusion syndrome or adverse neonatal outcomes.',
    'Calcium and vitamin D are essential nutrients for bone metabolism Vitamin D can either be obtained from dietary sources or cutaneous synthesis. The study was conducted in subtropic weather; therefore, some might believe that the levels of solar radiation would be sufficient in this area.To evaluate calcium and vitamin D supplementation in postmenopausal women with osteoporosis living in a sunny country.A 3-month controlled clinical trial with 64 postmenopausal women with osteoporosis, mean age 62 + or - 8 years. They were randomly assigned to either the supplement group, who received 1,200 mg of calcium carbonate and 400 IU (10 microg) of vitamin D(3,) or the control group. Dietary intake assessment was performed, bone mineral density and body composition were measured, and biochemical markers of bone metabolism were analyzed.Considering all participants at baseline, serum vitamin D was under 75 nmol/l in 91.4% of the participants. The concentration of serum 25(OH)D increased significantly (p = 0.023) after 3 months of supplementation from 46.67 + or - 13.97 to 59.47 + or - 17.50 nmol/l. However, the dose given was limited in effect, and 86.2% of the supplement group did not reach optimal levels of 25(OH)D. Parathyroid hormone was elevated in 22.4% of the study group. After the intervention period, mean parathyroid hormone tended to decrease in the supplement group (p = 0.063).',
]
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]

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Evaluation

Metrics

Triplet

—Dataset: medi-mteb-dev
—Evaluated with <code>TripletEvaluator</code>

Metric	Value
cosine_accuracy	0.9153

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Training Details

Training Datasets

NQ

—Dataset: NQ
—Size: 49,548 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 11.77 tokens</li><li>max: 22 tokens</li></ul> | <ul><li>min: 113 tokens</li><li>mean: 137.23 tokens</li><li>max: 220 tokens</li></ul> | <ul><li>min: 110 tokens</li><li>mean: 138.25 tokens</li><li>max: 239 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

pubmed

—Dataset: pubmed
—Size: 29,716 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 22.99 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 78 tokens</li><li>mean: 240.63 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 50 tokens</li><li>mean: 239.04 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

spectertraintriples

—Dataset: spectertraintriples
—Size: 49,548 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 15.21 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 13.87 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 16.01 tokens</li><li>max: 70 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

S2ORCcitationsabstracts

—Dataset: S2ORCcitationsabstracts
—Size: 99,032 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 22 tokens</li><li>mean: 198.64 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 30 tokens</li><li>mean: 203.8 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 203.03 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

fever

—Dataset: fever
—Size: 74,258 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 12.23 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 111.79 tokens</li><li>max: 150 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 113.24 tokens</li><li>max: 179 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

gooaq_pairs

—Dataset: gooaq_pairs
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 11.86 tokens</li><li>max: 26 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 59.94 tokens</li><li>max: 138 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 63.35 tokens</li><li>max: 149 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

codesearchnet

—Dataset: codesearchnet
—Size: 14,890 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 29.54 tokens</li><li>max: 124 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 132.91 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 163.79 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

wikihow

—Dataset: wikihow
—Size: 5,006 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 8.16 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 44.62 tokens</li><li>max: 117 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 36.33 tokens</li><li>max: 100 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

WikiAnswers

—Dataset: WikiAnswers
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 12.83 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 12.7 tokens</li><li>max: 36 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 13.12 tokens</li><li>max: 42 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

eli5questionanswer

—Dataset: eli5questionanswer
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 20.98 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 103.88 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 111.38 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

amazon-qa

—Dataset: amazon-qa
—Size: 99,032 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 23.07 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 54.48 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 61.35 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

medmcqa

—Dataset: medmcqa
—Size: 29,716 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 19.86 tokens</li><li>max: 176 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 113.43 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 108.04 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

zeroshot

—Dataset: zeroshot
—Size: 14,890 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 8.65 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 112.61 tokens</li><li>max: 163 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 117.07 tokens</li><li>max: 214 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

TriviaQA_pairs

—Dataset: TriviaQA_pairs
—Size: 49,548 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 19.79 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 245.73 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 26 tokens</li><li>mean: 231.5 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

PAQ_pairs

—Dataset: PAQ_pairs
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 12.67 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 110 tokens</li><li>mean: 135.61 tokens</li><li>max: 223 tokens</li></ul> | <ul><li>min: 111 tokens</li><li>mean: 135.86 tokens</li><li>max: 254 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

stackexchangeduplicatequestionstitle-bodytitle-body

—Dataset: stackexchangeduplicatequestionstitle-bodytitle-body
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 21 tokens</li><li>mean: 146.64 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 141.12 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 200.51 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

trex

—Dataset: trex
—Size: 29,716 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 9.43 tokens</li><li>max: 20 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 102.9 tokens</li><li>max: 166 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 118.59 tokens</li><li>max: 236 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

flickr30k_captions

—Dataset: flickr30k_captions
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 15.87 tokens</li><li>max: 61 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 15.83 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.13 tokens</li><li>max: 61 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

hotpotqa

—Dataset: hotpotqa
—Size: 39,600 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 24.46 tokens</li><li>max: 97 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 113.58 tokens</li><li>max: 176 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 114.85 tokens</li><li>max: 167 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task671ambigqatext_generation

—Dataset: task671ambigqatext_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 11 tokens</li><li>mean: 12.64 tokens</li><li>max: 26 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 12.44 tokens</li><li>max: 23 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 12.2 tokens</li><li>max: 19 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task061ropesanswer_generation

—Dataset: task061ropesanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 117 tokens</li><li>mean: 209.31 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 117 tokens</li><li>mean: 208.62 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 119 tokens</li><li>mean: 211.39 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task285imdbanswer_generation

—Dataset: task285imdbanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 46 tokens</li><li>mean: 209.96 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 49 tokens</li><li>mean: 205.18 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 209.96 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task905hatespeechoffensiveclassification

—Dataset: task905hatespeechoffensiveclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 15 tokens</li><li>mean: 41.48 tokens</li><li>max: 164 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 40.59 tokens</li><li>max: 198 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 32.37 tokens</li><li>max: 135 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task566circaclassification

—Dataset: task566circaclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 20 tokens</li><li>mean: 27.85 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 27.3 tokens</li><li>max: 44 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 27.5 tokens</li><li>max: 47 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task184snlientailmenttoneutraltextmodification

—Dataset: task184snlientailmenttoneutraltextmodification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 29.79 tokens</li><li>max: 72 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 28.88 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 30.16 tokens</li><li>max: 100 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task280stereosetclassificationstereotypetype

—Dataset: task280stereosetclassificationstereotypetype
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 18.4 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 16.82 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 16.81 tokens</li><li>max: 51 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1599smcalflowclassification

—Dataset: task1599smcalflowclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 11.32 tokens</li><li>max: 37 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 10.48 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 16.23 tokens</li><li>max: 45 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1384dealornodialog_classification

—Dataset: task1384dealornodialog_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 59.18 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 58.75 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 58.81 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task591sciqanswer_generation

—Dataset: task591sciqanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 17.64 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.17 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 16.76 tokens</li><li>max: 75 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task823peixian-rtgendersentiment_analysis

—Dataset: task823peixian-rtgendersentiment_analysis
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 57.03 tokens</li><li>max: 129 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 59.85 tokens</li><li>max: 153 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 60.39 tokens</li><li>max: 169 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task023cosmosqaquestion_generation

—Dataset: task023cosmosqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 35 tokens</li><li>mean: 79.22 tokens</li><li>max: 159 tokens</li></ul> | <ul><li>min: 34 tokens</li><li>mean: 80.25 tokens</li><li>max: 165 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 79.05 tokens</li><li>max: 161 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task900freebaseqacategoryclassification

—Dataset: task900freebaseqacategoryclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 20.33 tokens</li><li>max: 88 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 18.3 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 19.08 tokens</li><li>max: 69 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task924event2mindword_generation

—Dataset: task924event2mindword_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 32.19 tokens</li><li>max: 64 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 32.09 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 31.45 tokens</li><li>max: 68 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task152tomqafindlocationeasy_noise

—Dataset: task152tomqafindlocationeasy_noise
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 37 tokens</li><li>mean: 52.67 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 52.21 tokens</li><li>max: 78 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 52.78 tokens</li><li>max: 82 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1368healthfactsentence_generation

—Dataset: task1368healthfactsentence_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 91 tokens</li><li>mean: 240.92 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 84 tokens</li><li>mean: 239.86 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 97 tokens</li><li>mean: 245.16 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1661superglue_classification

—Dataset: task1661superglue_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 35 tokens</li><li>mean: 140.96 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 144.29 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 143.59 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1187politifactclassification

—Dataset: task1187politifactclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 33.19 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 31.7 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 31.87 tokens</li><li>max: 71 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1728webnlgdatato_text

—Dataset: task1728webnlgdatato_text
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 42.96 tokens</li><li>max: 152 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 46.52 tokens</li><li>max: 152 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 42.39 tokens</li><li>max: 152 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task112assetsimplesentenceidentification

—Dataset: task112assetsimplesentenceidentification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 51.98 tokens</li><li>max: 136 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 51.84 tokens</li><li>max: 144 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 51.97 tokens</li><li>max: 114 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1340msrtextcompressioncompression

—Dataset: task1340msrtextcompressioncompression
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 42.15 tokens</li><li>max: 116 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 44.46 tokens</li><li>max: 133 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.14 tokens</li><li>max: 141 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task072abductivenlianswer_generation

—Dataset: task072abductivenlianswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 26.9 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 26.28 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 26.46 tokens</li><li>max: 55 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1504hatexplainanswer_generation

—Dataset: task1504hatexplainanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 29.09 tokens</li><li>max: 72 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 24.67 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 27.96 tokens</li><li>max: 67 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task684onlineprivacypolicytextinformationtype_generation

—Dataset: task684onlineprivacypolicytextinformationtype_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 30.02 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 30.19 tokens</li><li>max: 61 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 30.18 tokens</li><li>max: 68 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1290xsumsummarization

—Dataset: task1290xsumsummarization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 39 tokens</li><li>mean: 226.27 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 50 tokens</li><li>mean: 228.93 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 34 tokens</li><li>mean: 229.41 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task075squad1.1answer_generation

—Dataset: task075squad1.1answer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 48 tokens</li><li>mean: 168.58 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 45 tokens</li><li>mean: 172.1 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 181.15 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1587scifactclassification

—Dataset: task1587scifactclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 88 tokens</li><li>mean: 242.35 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 90 tokens</li><li>mean: 246.75 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 86 tokens</li><li>mean: 244.87 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task384socialiqaquestion_classification

—Dataset: task384socialiqaquestion_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 35.44 tokens</li><li>max: 78 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 34.35 tokens</li><li>max: 59 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 34.51 tokens</li><li>max: 57 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1555scitailanswer_generation

—Dataset: task1555scitailanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 36.72 tokens</li><li>max: 90 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 36.31 tokens</li><li>max: 80 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 36.73 tokens</li><li>max: 92 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1532dailydialogemotionclassification

—Dataset: task1532dailydialogemotionclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 137.07 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 140.81 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 132.89 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task239tweetqaanswer_generation

—Dataset: task239tweetqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 28 tokens</li><li>mean: 55.78 tokens</li><li>max: 85 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 56.32 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 55.92 tokens</li><li>max: 81 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task596mochaquestion_generation

—Dataset: task596mochaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 34 tokens</li><li>mean: 80.49 tokens</li><li>max: 163 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 95.93 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 44.93 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1411dartsubject_identification

—Dataset: task1411dartsubject_identification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 14.86 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 14.02 tokens</li><li>max: 37 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 14.25 tokens</li><li>max: 38 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1359numersenseanswergeneration

—Dataset: task1359numersenseanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 18.67 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 18.43 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 18.34 tokens</li><li>max: 30 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task329gapclassification

—Dataset: task329gapclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 40 tokens</li><li>mean: 122.88 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 62 tokens</li><li>mean: 127.47 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 58 tokens</li><li>mean: 127.71 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task220rocstoriestitle_classification

—Dataset: task220rocstoriestitle_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 53 tokens</li><li>mean: 80.81 tokens</li><li>max: 116 tokens</li></ul> | <ul><li>min: 51 tokens</li><li>mean: 81.08 tokens</li><li>max: 108 tokens</li></ul> | <ul><li>min: 55 tokens</li><li>mean: 79.99 tokens</li><li>max: 115 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task316crows-pairsclassification_stereotype

—Dataset: task316crows-pairsclassification_stereotype
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 19.78 tokens</li><li>max: 51 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 18.31 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.87 tokens</li><li>max: 52 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task495semevalheadline_classification

—Dataset: task495semevalheadline_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 24.57 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 24.29 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 24.14 tokens</li><li>max: 38 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1168browncoarsepostagging

—Dataset: task1168browncoarsepostagging
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 43.61 tokens</li><li>max: 142 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 42.6 tokens</li><li>max: 197 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 44.23 tokens</li><li>max: 197 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task348squad2.0unanswerablequestiongeneration

—Dataset: task348squad2.0unanswerablequestiongeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 30 tokens</li><li>mean: 153.88 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 161.26 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 166.13 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task049multircquestionsneededto_answer

—Dataset: task049multircquestionsneededto_answer
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 174 tokens</li><li>mean: 252.7 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 169 tokens</li><li>mean: 252.85 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 178 tokens</li><li>mean: 252.93 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1534dailydialogquestionclassification

—Dataset: task1534dailydialogquestionclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 124.7 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 130.68 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 135.16 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task322jigsawclassification_threat

—Dataset: task322jigsawclassification_threat
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 54.9 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 62.74 tokens</li><li>max: 249 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 61.92 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task295semeval2020task4commonsense_reasoning

—Dataset: task295semeval2020task4commonsense_reasoning
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 25 tokens</li><li>mean: 45.35 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 44.74 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 44.53 tokens</li><li>max: 88 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task186snlicontradictiontoentailmenttextmodification

—Dataset: task186snlicontradictiontoentailmenttextmodification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 31.09 tokens</li><li>max: 102 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 30.26 tokens</li><li>max: 65 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 32.22 tokens</li><li>max: 67 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task034winograndequestionmodificationobject

—Dataset: task034winograndequestionmodificationobject
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 29 tokens</li><li>mean: 36.26 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 35.64 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 34.85 tokens</li><li>max: 55 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task160replaceletterina_sentence

—Dataset: task160replaceletterina_sentence
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 29 tokens</li><li>mean: 32.03 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.76 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 31.77 tokens</li><li>max: 48 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task469mrqaanswer_generation

—Dataset: task469mrqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 27 tokens</li><li>mean: 182.13 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 180.78 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 183.72 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task105storycloze-rocstoriessentencegeneration

—Dataset: task105storycloze-rocstoriessentencegeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 36 tokens</li><li>mean: 55.65 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 55.02 tokens</li><li>max: 76 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 55.88 tokens</li><li>max: 76 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task649raceblankquestiongeneration

—Dataset: task649raceblankquestiongeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 36 tokens</li><li>mean: 252.95 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 252.78 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 157 tokens</li><li>mean: 253.91 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1536dailydialoghappinessclassification

—Dataset: task1536dailydialoghappinessclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 127.91 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 134.02 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 143.7 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task683onlineprivacypolicytextpurposeanswer_generation

—Dataset: task683onlineprivacypolicytextpurposeanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 30.09 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 30.5 tokens</li><li>max: 64 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 30.07 tokens</li><li>max: 68 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task024cosmosqaanswer_generation

—Dataset: task024cosmosqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 45 tokens</li><li>mean: 92.62 tokens</li><li>max: 176 tokens</li></ul> | <ul><li>min: 47 tokens</li><li>mean: 93.35 tokens</li><li>max: 174 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 94.9 tokens</li><li>max: 183 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task584udepsengfinepos_tagging

—Dataset: task584udepsengfinepos_tagging
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 40.09 tokens</li><li>max: 120 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 39.35 tokens</li><li>max: 186 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.38 tokens</li><li>max: 148 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task066timetravelbinaryconsistencyclassification

—Dataset: task066timetravelbinaryconsistencyclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 42 tokens</li><li>mean: 66.69 tokens</li><li>max: 93 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 67.34 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 45 tokens</li><li>mean: 67.19 tokens</li><li>max: 92 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task413mickeyensentenceperturbation_generation

—Dataset: task413mickeyensentenceperturbation_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 13.71 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 13.75 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 13.29 tokens</li><li>max: 20 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task182duorcquestion_generation

—Dataset: task182duorcquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 99 tokens</li><li>mean: 242.77 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 120 tokens</li><li>mean: 246.47 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 99 tokens</li><li>mean: 246.38 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task028dropanswer_generation

—Dataset: task028dropanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 76 tokens</li><li>mean: 230.94 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 86 tokens</li><li>mean: 234.89 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 81 tokens</li><li>mean: 235.48 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1601webquestionsanswer_generation

—Dataset: task1601webquestionsanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 16.49 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 16.71 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 16.76 tokens</li><li>max: 27 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1295adversarialqaquestionanswering

—Dataset: task1295adversarialqaquestionanswering
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 45 tokens</li><li>mean: 163.69 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 54 tokens</li><li>mean: 166.23 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 166.52 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task201mnlineutral_classification

—Dataset: task201mnlineutral_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 72.97 tokens</li><li>max: 218 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 73.29 tokens</li><li>max: 170 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 72.24 tokens</li><li>max: 205 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task038qasccombined_fact

—Dataset: task038qasccombined_fact
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 31.25 tokens</li><li>max: 57 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 30.61 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 30.86 tokens</li><li>max: 53 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task293storycommonsenseemotiontextgeneration

—Dataset: task293storycommonsenseemotiontextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 40.25 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 40.27 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 38.11 tokens</li><li>max: 86 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task572recipenlgtextgeneration

—Dataset: task572recipenlgtextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 115.66 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 122.27 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 124.11 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task517emoclassifyemotionof_dialogue

—Dataset: task517emoclassifyemotionof_dialogue
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 18.13 tokens</li><li>max: 78 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.07 tokens</li><li>max: 59 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 18.5 tokens</li><li>max: 67 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task382hybridqaanswer_generation

—Dataset: task382hybridqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 29 tokens</li><li>mean: 42.28 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 41.56 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 41.74 tokens</li><li>max: 75 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task176breakdecompose_questions

—Dataset: task176breakdecompose_questions
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 17.48 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.2 tokens</li><li>max: 39 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 15.6 tokens</li><li>max: 38 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1291multinews_summarization

—Dataset: task1291multinews_summarization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 116 tokens</li><li>mean: 255.49 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 146 tokens</li><li>mean: 255.55 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 68 tokens</li><li>mean: 251.87 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task155countnouns_verbs

—Dataset: task155countnouns_verbs
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 23 tokens</li><li>mean: 27.05 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 26.81 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 26.98 tokens</li><li>max: 46 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task031winograndequestiongenerationobject

—Dataset: task031winograndequestiongenerationobject
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 7.42 tokens</li><li>max: 11 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 7.3 tokens</li><li>max: 11 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 7.25 tokens</li><li>max: 11 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task279stereosetclassification_stereotype

—Dataset: task279stereosetclassification_stereotype
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 17.85 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 15.47 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.28 tokens</li><li>max: 50 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1336peixianequityevaluationcorpusgenderclassifier

—Dataset: task1336peixianequityevaluationcorpusgenderclassifier
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 9.66 tokens</li><li>max: 17 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.61 tokens</li><li>max: 16 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.72 tokens</li><li>max: 16 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task508scruplesdilemmasmoreethical_isidentifiable

—Dataset: task508scruplesdilemmasmoreethical_isidentifiable
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 29.84 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 28.5 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 28.66 tokens</li><li>max: 86 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task518emodifferentdialogueemotions

—Dataset: task518emodifferentdialogueemotions
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 28 tokens</li><li>mean: 47.9 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 45.44 tokens</li><li>max: 116 tokens</li></ul> | <ul><li>min: 26 tokens</li><li>mean: 46.17 tokens</li><li>max: 123 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task077splashexplanationtosql

—Dataset: task077splashexplanationtosql
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 39.24 tokens</li><li>max: 126 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 39.15 tokens</li><li>max: 126 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 35.65 tokens</li><li>max: 111 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task923event2mindclassifier

—Dataset: task923event2mindclassifier
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 20.63 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 18.75 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 19.63 tokens</li><li>max: 46 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task470mrqaquestion_generation

—Dataset: task470mrqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 173.13 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 175.67 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 181.16 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task638multiwoz_classification

—Dataset: task638multiwoz_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 78 tokens</li><li>mean: 223.5 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 76 tokens</li><li>mean: 220.15 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 64 tokens</li><li>mean: 220.29 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1412webquestionsquestionanswering

—Dataset: task1412webquestionsquestionanswering
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 10.32 tokens</li><li>max: 17 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.23 tokens</li><li>max: 17 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.06 tokens</li><li>max: 16 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task847pubmedqaquestion_generation

—Dataset: task847pubmedqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 21 tokens</li><li>mean: 249.15 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 21 tokens</li><li>mean: 248.61 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 248.86 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task678ollieactualrelationshipanswer_generation

—Dataset: task678ollieactualrelationshipanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 20 tokens</li><li>mean: 40.63 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 38.38 tokens</li><li>max: 102 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 40.99 tokens</li><li>max: 104 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task290tellmewhyquestion_answerability

—Dataset: task290tellmewhyquestion_answerability
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 37 tokens</li><li>mean: 62.58 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 62.21 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 62.91 tokens</li><li>max: 95 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task575airdialogue_classification

—Dataset: task575airdialogue_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 14.18 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 13.6 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 12.3 tokens</li><li>max: 42 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task189snlineutraltocontradictiontextmodification

—Dataset: task189snlineutraltocontradictiontextmodification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 31.89 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 30.66 tokens</li><li>max: 57 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 33.29 tokens</li><li>max: 105 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task026dropquestion_generation

—Dataset: task026dropquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 82 tokens</li><li>mean: 219.82 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 57 tokens</li><li>mean: 222.71 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 96 tokens</li><li>mean: 232.56 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task162countwordsstartingwith_letter

—Dataset: task162countwordsstartingwith_letter
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 28 tokens</li><li>mean: 32.16 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.77 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.65 tokens</li><li>max: 46 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task079conalaconcat_strings

—Dataset: task079conalaconcat_strings
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 11 tokens</li><li>mean: 39.94 tokens</li><li>max: 76 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 34.24 tokens</li><li>max: 80 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 33.86 tokens</li><li>max: 76 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task610conllppner

—Dataset: task610conllppner
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 19.74 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 20.71 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 14.24 tokens</li><li>max: 54 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task046miscellaneousquestion_typing

—Dataset: task046miscellaneousquestion_typing
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 25.26 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 24.84 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 25.2 tokens</li><li>max: 57 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task197mnlidomainanswergeneration

—Dataset: task197mnlidomainanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 15 tokens</li><li>mean: 44.08 tokens</li><li>max: 197 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 44.95 tokens</li><li>max: 211 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 39.27 tokens</li><li>max: 115 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1325qazrequestiongenerationonsubject_relation

—Dataset: task1325qazrequestiongenerationonsubject_relation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 50.63 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 49.26 tokens</li><li>max: 180 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 54.42 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task430sentevalsubject_count

—Dataset: task430sentevalsubject_count
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 17.26 tokens</li><li>max: 35 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.37 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 16.07 tokens</li><li>max: 34 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task672_nummersense

—Dataset: task672_nummersense
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 15.66 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.43 tokens</li><li>max: 27 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.25 tokens</li><li>max: 30 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task402grailqaparaphrase_generation

—Dataset: task402grailqaparaphrase_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 23 tokens</li><li>mean: 129.84 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 139.54 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 136.75 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task904hatespeechoffensiveclassification

—Dataset: task904hatespeechoffensiveclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 34.35 tokens</li><li>max: 157 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 34.38 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 27.8 tokens</li><li>max: 148 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task192hotpotqasentence_generation

—Dataset: task192hotpotqasentence_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 37 tokens</li><li>mean: 124.56 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 123.35 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 132.67 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task069abductivenliclassification

—Dataset: task069abductivenliclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 33 tokens</li><li>mean: 52.03 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 51.87 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 52.01 tokens</li><li>max: 95 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task574airdialoguesentencegeneration

—Dataset: task574airdialoguesentencegeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 54 tokens</li><li>mean: 144.28 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 57 tokens</li><li>mean: 144.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 66 tokens</li><li>mean: 148.22 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task187snlientailmenttocontradictiontextmodification

—Dataset: task187snlientailmenttocontradictiontextmodification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 30.35 tokens</li><li>max: 69 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 29.87 tokens</li><li>max: 104 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 29.47 tokens</li><li>max: 71 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task749glucosereversecauseemotion_detection

—Dataset: task749glucosereversecauseemotion_detection
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 38 tokens</li><li>mean: 67.51 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 67.07 tokens</li><li>max: 104 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 68.56 tokens</li><li>max: 107 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1552scitailquestion_generation

—Dataset: task1552scitailquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 18.34 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.5 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.81 tokens</li><li>max: 54 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task750aquamultiplechoiceanswering

—Dataset: task750aquamultiplechoiceanswering
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 33 tokens</li><li>mean: 69.8 tokens</li><li>max: 194 tokens</li></ul> | <ul><li>min: 32 tokens</li><li>mean: 68.34 tokens</li><li>max: 194 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 68.21 tokens</li><li>max: 165 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task327jigsawclassification_toxic

—Dataset: task327jigsawclassification_toxic
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 36.99 tokens</li><li>max: 234 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 41.72 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 44.88 tokens</li><li>max: 244 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1502hatexplainclassification

—Dataset: task1502hatexplainclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 28.7 tokens</li><li>max: 73 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 26.89 tokens</li><li>max: 110 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 26.9 tokens</li><li>max: 90 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task328jigsawclassification_insult

—Dataset: task328jigsawclassification_insult
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 50.28 tokens</li><li>max: 247 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 60.6 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 64.07 tokens</li><li>max: 249 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task304numericfusedheadresolution

—Dataset: task304numericfusedheadresolution
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 15 tokens</li><li>mean: 116.82 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 118.84 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 131.78 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1293kilttaskshotpotqaquestion_answering

—Dataset: task1293kilttaskshotpotqaquestion_answering
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 24.8 tokens</li><li>max: 114 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 24.33 tokens</li><li>max: 114 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 23.79 tokens</li><li>max: 84 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task216rocstoriescorrectanswergeneration

—Dataset: task216rocstoriescorrectanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 39 tokens</li><li>mean: 59.37 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 58.11 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 58.26 tokens</li><li>max: 95 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1326qazrequestiongenerationfromanswer

—Dataset: task1326qazrequestiongenerationfromanswer
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 46.71 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 45.51 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 49.23 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1338peixianequityevaluationcorpussentimentclassifier

—Dataset: task1338peixianequityevaluationcorpussentimentclassifier
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 9.72 tokens</li><li>max: 16 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.73 tokens</li><li>max: 16 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.61 tokens</li><li>max: 17 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1729personachatgenerate_next

—Dataset: task1729personachatgenerate_next
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 44 tokens</li><li>mean: 147.13 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 142.78 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 50 tokens</li><li>mean: 144.33 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1202atomicclassification_xneed

—Dataset: task1202atomicclassification_xneed
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 19.54 tokens</li><li>max: 32 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.41 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.22 tokens</li><li>max: 28 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task400pawsparaphrase_classification

—Dataset: task400pawsparaphrase_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 19 tokens</li><li>mean: 52.25 tokens</li><li>max: 97 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 51.75 tokens</li><li>max: 98 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 52.95 tokens</li><li>max: 97 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task502scruplesanecdoteswhoiswrongverification

—Dataset: task502scruplesanecdoteswhoiswrongverification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 230.24 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 236.91 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 235.21 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task088identifytypo_verification

—Dataset: task088identifytypo_verification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 11 tokens</li><li>mean: 15.12 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 15.06 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 15.45 tokens</li><li>max: 47 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task221rocstoriestwochoiceclassification

—Dataset: task221rocstoriestwochoiceclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 47 tokens</li><li>mean: 72.36 tokens</li><li>max: 108 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 72.48 tokens</li><li>max: 109 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 73.1 tokens</li><li>max: 108 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task200mnlientailment_classification

—Dataset: task200mnlientailment_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 72.71 tokens</li><li>max: 198 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 73.01 tokens</li><li>max: 224 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 73.39 tokens</li><li>max: 226 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task074squad1.1question_generation

—Dataset: task074squad1.1question_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 30 tokens</li><li>mean: 150.13 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 160.24 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 164.44 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task581socialiqaquestion_generation

—Dataset: task581socialiqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 26.5 tokens</li><li>max: 69 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 25.65 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 25.77 tokens</li><li>max: 48 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1186nnehrngo_classification

—Dataset: task1186nnehrngo_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 19 tokens</li><li>mean: 33.8 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 33.54 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 33.65 tokens</li><li>max: 77 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task898freebaseqaanswergeneration

—Dataset: task898freebaseqaanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 19.39 tokens</li><li>max: 125 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.69 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.38 tokens</li><li>max: 79 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1408dartsimilarity_classification

—Dataset: task1408dartsimilarity_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 22 tokens</li><li>mean: 59.5 tokens</li><li>max: 147 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 61.89 tokens</li><li>max: 154 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 48.9 tokens</li><li>max: 124 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task168strategyqaquestion_decomposition

—Dataset: task168strategyqaquestion_decomposition
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 42 tokens</li><li>mean: 79.99 tokens</li><li>max: 181 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 79.63 tokens</li><li>max: 179 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 76.6 tokens</li><li>max: 166 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1357xlsumsummary_generation

—Dataset: task1357xlsumsummary_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 67 tokens</li><li>mean: 241.38 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 69 tokens</li><li>mean: 243.16 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 67 tokens</li><li>mean: 246.78 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task390torquetextspanselection

—Dataset: task390torquetextspanselection
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 47 tokens</li><li>mean: 110.58 tokens</li><li>max: 196 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 110.41 tokens</li><li>max: 195 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 111.15 tokens</li><li>max: 196 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task165mcscriptquestionansweringcommonsense

—Dataset: task165mcscriptquestionansweringcommonsense
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 147 tokens</li><li>mean: 199.7 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 145 tokens</li><li>mean: 198.04 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 147 tokens</li><li>mean: 200.11 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1533dailydialogformalclassification

—Dataset: task1533dailydialogformalclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 130.14 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 136.4 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 137.09 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task002quorefanswer_generation

—Dataset: task002quorefanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 214 tokens</li><li>mean: 255.53 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 214 tokens</li><li>mean: 255.5 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 224 tokens</li><li>mean: 255.58 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1297qascquestion_answering

—Dataset: task1297qascquestion_answering
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 61 tokens</li><li>mean: 84.44 tokens</li><li>max: 134 tokens</li></ul> | <ul><li>min: 59 tokens</li><li>mean: 85.31 tokens</li><li>max: 130 tokens</li></ul> | <ul><li>min: 58 tokens</li><li>mean: 84.94 tokens</li><li>max: 125 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task305jeopardyanswergenerationnormal

—Dataset: task305jeopardyanswergenerationnormal
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 27.68 tokens</li><li>max: 59 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 27.48 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 27.42 tokens</li><li>max: 46 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task029winograndefull_object

—Dataset: task029winograndefull_object
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 7.38 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 7.34 tokens</li><li>max: 11 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 7.24 tokens</li><li>max: 10 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1327qazreanswergenerationfromquestion

—Dataset: task1327qazreanswergenerationfromquestion
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 54.88 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 52.02 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 56.19 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task326jigsawclassification_obscene

—Dataset: task326jigsawclassification_obscene
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 63.85 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 76.17 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 72.28 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1542everyithelementfrom_starting

—Dataset: task1542everyithelementfrom_starting
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 125.18 tokens</li><li>max: 245 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 123.56 tokens</li><li>max: 244 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 121.24 tokens</li><li>max: 238 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task570recipenlgnergeneration

—Dataset: task570recipenlgnergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 74.84 tokens</li><li>max: 250 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 73.97 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 76.51 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1409darttext_generation

—Dataset: task1409darttext_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 67.5 tokens</li><li>max: 174 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 72.28 tokens</li><li>max: 170 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 67.22 tokens</li><li>max: 164 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task401numericfusedheadreference

—Dataset: task401numericfusedheadreference
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 109.31 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 114.71 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 120.55 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task846pubmedqaclassification

—Dataset: task846pubmedqaclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 32 tokens</li><li>mean: 86.22 tokens</li><li>max: 246 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 85.64 tokens</li><li>max: 225 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 94.03 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1712pokiclassification

—Dataset: task1712pokiclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 53.16 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 56.97 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 63.57 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task344hybridqaanswer_generation

—Dataset: task344hybridqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 22.21 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 21.92 tokens</li><li>max: 58 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 22.19 tokens</li><li>max: 55 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task875emotionclassification

—Dataset: task875emotionclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 23.18 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 18.52 tokens</li><li>max: 63 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 20.35 tokens</li><li>max: 68 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1214atomicclassification_xwant

—Dataset: task1214atomicclassification_xwant
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 19.64 tokens</li><li>max: 32 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.36 tokens</li><li>max: 29 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.54 tokens</li><li>max: 31 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task106scruplesethical_judgment

—Dataset: task106scruplesethical_judgment
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 30.0 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 28.89 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 28.73 tokens</li><li>max: 58 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task238iircanswerfrompassageanswergeneration

—Dataset: task238iircanswerfrompassageanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 138 tokens</li><li>mean: 242.78 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 165 tokens</li><li>mean: 242.57 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 173 tokens</li><li>mean: 243.0 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1391winograndeeasyanswergeneration

—Dataset: task1391winograndeeasyanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 26 tokens</li><li>mean: 31.63 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>min: 26 tokens</li><li>mean: 31.36 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 31.3 tokens</li><li>max: 49 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task195sentiment140classification

—Dataset: task195sentiment140classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 22.47 tokens</li><li>max: 118 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 18.84 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 21.25 tokens</li><li>max: 51 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task163countwordsendingwith_letter

—Dataset: task163countwordsendingwith_letter
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 28 tokens</li><li>mean: 32.05 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.69 tokens</li><li>max: 57 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.58 tokens</li><li>max: 43 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task579socialiqaclassification

—Dataset: task579socialiqaclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 39 tokens</li><li>mean: 54.11 tokens</li><li>max: 132 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 53.52 tokens</li><li>max: 103 tokens</li></ul> | <ul><li>min: 40 tokens</li><li>mean: 54.12 tokens</li><li>max: 84 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task569recipenlgtextgeneration

—Dataset: task569recipenlgtextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 25 tokens</li><li>mean: 192.16 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 55 tokens</li><li>mean: 193.74 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 199.11 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1602webquestionquestion_genreation

—Dataset: task1602webquestionquestion_genreation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 23.95 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 24.6 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 22.6 tokens</li><li>max: 120 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task747glucosecauseemotiondetection

—Dataset: task747glucosecauseemotiondetection
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 35 tokens</li><li>mean: 68.23 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 68.25 tokens</li><li>max: 108 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 68.75 tokens</li><li>max: 99 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task219rocstoriestitleanswergeneration

—Dataset: task219rocstoriestitleanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 42 tokens</li><li>mean: 67.62 tokens</li><li>max: 97 tokens</li></ul> | <ul><li>min: 45 tokens</li><li>mean: 66.65 tokens</li><li>max: 97 tokens</li></ul> | <ul><li>min: 41 tokens</li><li>mean: 66.89 tokens</li><li>max: 96 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task178quartzquestion_answering

—Dataset: task178quartzquestion_answering
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 28 tokens</li><li>mean: 57.96 tokens</li><li>max: 110 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 57.18 tokens</li><li>max: 111 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 56.74 tokens</li><li>max: 102 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task103facts2storylongtextgeneration

—Dataset: task103facts2storylongtextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 52 tokens</li><li>mean: 80.34 tokens</li><li>max: 143 tokens</li></ul> | <ul><li>min: 51 tokens</li><li>mean: 82.24 tokens</li><li>max: 157 tokens</li></ul> | <ul><li>min: 49 tokens</li><li>mean: 78.57 tokens</li><li>max: 136 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task301recordquestion_generation

—Dataset: task301recordquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 140 tokens</li><li>mean: 210.76 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 139 tokens</li><li>mean: 209.62 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 143 tokens</li><li>mean: 209.06 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1369healthfactsentence_generation

—Dataset: task1369healthfactsentence_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 110 tokens</li><li>mean: 243.14 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 101 tokens</li><li>mean: 242.95 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 113 tokens</li><li>mean: 251.89 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task515sentevaloddwordout

—Dataset: task515sentevaloddwordout
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 19.75 tokens</li><li>max: 36 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.02 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 18.93 tokens</li><li>max: 35 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task496semevalanswer_generation

—Dataset: task496semevalanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 28.06 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 27.74 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 27.69 tokens</li><li>max: 45 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1658billsumsummarization

—Dataset: task1658billsumsummarization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 256 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 256 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 256 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1204atomicclassification_hinderedby

—Dataset: task1204atomicclassification_hinderedby
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 21.98 tokens</li><li>max: 35 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 22.01 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 21.48 tokens</li><li>max: 38 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1392supergluemultircanswerverification

—Dataset: task1392supergluemultircanswerverification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 128 tokens</li><li>mean: 241.47 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 127 tokens</li><li>mean: 241.68 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 136 tokens</li><li>mean: 241.8 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task306jeopardyanswergenerationdouble

—Dataset: task306jeopardyanswergenerationdouble
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 27.73 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 27.13 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 27.69 tokens</li><li>max: 47 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1286openbookqaquestion_answering

—Dataset: task1286openbookqaquestion_answering
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 22 tokens</li><li>mean: 39.38 tokens</li><li>max: 85 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 38.71 tokens</li><li>max: 96 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 38.22 tokens</li><li>max: 89 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task159checkfrequencyofwordsinsentence_pair

—Dataset: task159checkfrequencyofwordsinsentence_pair
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 44 tokens</li><li>mean: 50.34 tokens</li><li>max: 67 tokens</li></ul> | <ul><li>min: 44 tokens</li><li>mean: 50.29 tokens</li><li>max: 67 tokens</li></ul> | <ul><li>min: 44 tokens</li><li>mean: 50.51 tokens</li><li>max: 66 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task151tomqafindlocationeasy_clean

—Dataset: task151tomqafindlocationeasy_clean
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 37 tokens</li><li>mean: 50.63 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 50.35 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 50.53 tokens</li><li>max: 74 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task323jigsawclassificationsexuallyexplicit

—Dataset: task323jigsawclassificationsexuallyexplicit
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 66.74 tokens</li><li>max: 248 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 77.15 tokens</li><li>max: 248 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 75.88 tokens</li><li>max: 251 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task037qascgeneraterelatedfact

—Dataset: task037qascgeneraterelatedfact
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 22.02 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 21.97 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 21.87 tokens</li><li>max: 40 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task027dropanswertypegeneration

—Dataset: task027dropanswertypegeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 87 tokens</li><li>mean: 229.25 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 74 tokens</li><li>mean: 230.99 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 71 tokens</li><li>mean: 232.46 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1596event2mindtextgeneration2

—Dataset: task1596event2mindtextgeneration2
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 9.92 tokens</li><li>max: 18 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.0 tokens</li><li>max: 19 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.05 tokens</li><li>max: 18 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task141odd-man-outclassification_category

—Dataset: task141odd-man-outclassification_category
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 18.45 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 18.39 tokens</li><li>max: 26 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 18.46 tokens</li><li>max: 25 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task194duorcanswer_generation

—Dataset: task194duorcanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 149 tokens</li><li>mean: 251.91 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 147 tokens</li><li>mean: 252.15 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 148 tokens</li><li>mean: 251.93 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task679hopeedienglishtext_classification

—Dataset: task679hopeedienglishtext_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 27.42 tokens</li><li>max: 199 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 26.83 tokens</li><li>max: 205 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 29.66 tokens</li><li>max: 194 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task246dreamquestion_generation

—Dataset: task246dreamquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 80.19 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 80.98 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 86.73 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1195disflqadisfluenttofluent_conversion

—Dataset: task1195disflqadisfluenttofluent_conversion
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 19.8 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 19.78 tokens</li><li>max: 40 tokens</li></ul> | <ul><li>min: 2 tokens</li><li>mean: 20.34 tokens</li><li>max: 44 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task065timetravelconsistentsentenceclassification

—Dataset: task065timetravelconsistentsentenceclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 55 tokens</li><li>mean: 79.64 tokens</li><li>max: 117 tokens</li></ul> | <ul><li>min: 51 tokens</li><li>mean: 79.21 tokens</li><li>max: 110 tokens</li></ul> | <ul><li>min: 53 tokens</li><li>mean: 79.78 tokens</li><li>max: 110 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task351winomtclassificationgenderidentifiability_anti

—Dataset: task351winomtclassificationgenderidentifiability_anti
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 21.77 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.69 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.8 tokens</li><li>max: 30 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task580socialiqaanswer_generation

—Dataset: task580socialiqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 35 tokens</li><li>mean: 52.45 tokens</li><li>max: 107 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 51.1 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 50.97 tokens</li><li>max: 87 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task583udepsengcoarsepos_tagging

—Dataset: task583udepsengcoarsepos_tagging
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 40.78 tokens</li><li>max: 185 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.09 tokens</li><li>max: 185 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.55 tokens</li><li>max: 185 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task202mnlicontradiction_classification

—Dataset: task202mnlicontradiction_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 74.1 tokens</li><li>max: 190 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 76.44 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 75.12 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task222rocstoriestwochioceslotting_classification

—Dataset: task222rocstoriestwochioceslotting_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 48 tokens</li><li>mean: 73.15 tokens</li><li>max: 105 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 73.22 tokens</li><li>max: 100 tokens</li></ul> | <ul><li>min: 49 tokens</li><li>mean: 72.05 tokens</li><li>max: 102 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task498scruplesanecdoteswhoiswrongclassification

—Dataset: task498scruplesanecdoteswhoiswrongclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 225.53 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 47 tokens</li><li>mean: 231.91 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 47 tokens</li><li>mean: 230.65 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task067abductivenlianswer_generation

—Dataset: task067abductivenlianswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 26.79 tokens</li><li>max: 40 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 26.12 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 26.33 tokens</li><li>max: 38 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task616colaclassification

—Dataset: task616colaclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 12.79 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 12.55 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 12.25 tokens</li><li>max: 29 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task286olidoffense_judgment

—Dataset: task286olidoffense_judgment
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 33.05 tokens</li><li>max: 145 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 31.09 tokens</li><li>max: 171 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 30.89 tokens</li><li>max: 169 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task188snlineutraltoentailmenttextmodification

—Dataset: task188snlineutraltoentailmenttextmodification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 31.81 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 31.16 tokens</li><li>max: 84 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 33.04 tokens</li><li>max: 84 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task223quartzexplanation_generation

—Dataset: task223quartzexplanation_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 31.45 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 31.82 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 29.1 tokens</li><li>max: 96 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task820protoqaanswer_generation

—Dataset: task820protoqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 14.84 tokens</li><li>max: 29 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 14.52 tokens</li><li>max: 27 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 14.23 tokens</li><li>max: 29 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task196sentiment140answer_generation

—Dataset: task196sentiment140answer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 36.15 tokens</li><li>max: 72 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 32.89 tokens</li><li>max: 61 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 36.14 tokens</li><li>max: 72 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1678mathqaanswer_selection

—Dataset: task1678mathqaanswer_selection
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 33 tokens</li><li>mean: 69.95 tokens</li><li>max: 177 tokens</li></ul> | <ul><li>min: 30 tokens</li><li>mean: 68.73 tokens</li><li>max: 146 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 69.24 tokens</li><li>max: 160 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task349squad2.0answerableunanswerablequestion_classification

—Dataset: task349squad2.0answerableunanswerablequestion_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 53 tokens</li><li>mean: 175.57 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 57 tokens</li><li>mean: 175.84 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 53 tokens</li><li>mean: 175.49 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task154tomqafindlocationhard_noise

—Dataset: task154tomqafindlocationhard_noise
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 129 tokens</li><li>mean: 175.63 tokens</li><li>max: 253 tokens</li></ul> | <ul><li>min: 126 tokens</li><li>mean: 175.85 tokens</li><li>max: 249 tokens</li></ul> | <ul><li>min: 128 tokens</li><li>mean: 177.2 tokens</li><li>max: 254 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task333hateevalclassificationhateen

—Dataset: task333hateevalclassificationhateen
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 38.62 tokens</li><li>max: 117 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 37.48 tokens</li><li>max: 109 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 36.83 tokens</li><li>max: 113 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task235iircquestionfromsubtextanswergeneration

—Dataset: task235iircquestionfromsubtextanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 52.54 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 50.77 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 55.44 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1554scitailclassification

—Dataset: task1554scitailclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 16.72 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 25.6 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 24.39 tokens</li><li>max: 59 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task210logic2textstructuredtextgeneration

—Dataset: task210logic2textstructuredtextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 31.83 tokens</li><li>max: 101 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 30.89 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 32.76 tokens</li><li>max: 89 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task035winograndequestionmodificationperson

—Dataset: task035winograndequestionmodificationperson
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 31 tokens</li><li>mean: 36.24 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 35.8 tokens</li><li>max: 55 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 35.46 tokens</li><li>max: 48 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task230iircpassage_classification

—Dataset: task230iircpassage_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 256 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 256 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 256 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1356xlsumtitle_generation

—Dataset: task1356xlsumtitle_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 59 tokens</li><li>mean: 239.39 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 58 tokens</li><li>mean: 241.03 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 64 tokens</li><li>mean: 248.12 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1726mathqacorrectanswergeneration

—Dataset: task1726mathqacorrectanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 43.95 tokens</li><li>max: 156 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 42.44 tokens</li><li>max: 129 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 42.8 tokens</li><li>max: 133 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task302recordclassification

—Dataset: task302recordclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 194 tokens</li><li>mean: 253.52 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 198 tokens</li><li>mean: 252.98 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 195 tokens</li><li>mean: 252.9 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task380boolqyesnoquestion

—Dataset: task380boolqyesnoquestion
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 26 tokens</li><li>mean: 133.18 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 26 tokens</li><li>mean: 138.06 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 137.06 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task212logic2textclassification

—Dataset: task212logic2textclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 33.56 tokens</li><li>max: 146 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 32.24 tokens</li><li>max: 146 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 33.17 tokens</li><li>max: 127 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task748glucosereversecauseevent_detection

—Dataset: task748glucosereversecauseevent_detection
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 35 tokens</li><li>mean: 68.0 tokens</li><li>max: 105 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 67.24 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 68.82 tokens</li><li>max: 105 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task834mathdatasetclassification

—Dataset: task834mathdatasetclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 27.89 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 28.2 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 27.11 tokens</li><li>max: 93 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task350winomtclassificationgenderidentifiability_pro

—Dataset: task350winomtclassificationgenderidentifiability_pro
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 21.8 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.62 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.81 tokens</li><li>max: 30 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task191hotpotqaquestion_generation

—Dataset: task191hotpotqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 198 tokens</li><li>mean: 255.91 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 238 tokens</li><li>mean: 255.94 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 255 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task236iircquestionfrompassageanswergeneration

—Dataset: task236iircquestionfrompassageanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 135 tokens</li><li>mean: 238.16 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 155 tokens</li><li>mean: 237.5 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 154 tokens</li><li>mean: 239.56 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task217rocstoriesorderinganswergeneration

—Dataset: task217rocstoriesorderinganswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 45 tokens</li><li>mean: 72.48 tokens</li><li>max: 107 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 72.44 tokens</li><li>max: 107 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 71.11 tokens</li><li>max: 105 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task568circaquestion_generation

—Dataset: task568circaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 9.65 tokens</li><li>max: 25 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 9.52 tokens</li><li>max: 20 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 8.98 tokens</li><li>max: 20 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task614glucosecauseeventdetection

—Dataset: task614glucosecauseeventdetection
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 39 tokens</li><li>mean: 67.94 tokens</li><li>max: 102 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 67.3 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 68.61 tokens</li><li>max: 103 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task361spolinyesandpromptresponse_classification

—Dataset: task361spolinyesandpromptresponse_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 46.89 tokens</li><li>max: 137 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 46.11 tokens</li><li>max: 119 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 47.3 tokens</li><li>max: 128 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task421persentsentencesentimentclassification

—Dataset: task421persentsentencesentimentclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 22 tokens</li><li>mean: 67.26 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 70.21 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 72.11 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task203mnlisentence_generation

—Dataset: task203mnlisentence_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 38.83 tokens</li><li>max: 175 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 35.68 tokens</li><li>max: 175 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 33.77 tokens</li><li>max: 170 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task420persentdocumentsentimentclassification

—Dataset: task420persentdocumentsentimentclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 22 tokens</li><li>mean: 222.98 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 233.17 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 228.48 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task153tomqafindlocationhard_clean

—Dataset: task153tomqafindlocationhard_clean
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 39 tokens</li><li>mean: 161.63 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 160.81 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 164.26 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task346hybridqaclassification

—Dataset: task346hybridqaclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 32.85 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 32.03 tokens</li><li>max: 63 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 31.88 tokens</li><li>max: 75 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1211atomicclassification_hassubevent

—Dataset: task1211atomicclassification_hassubevent
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 11 tokens</li><li>mean: 16.25 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 16.07 tokens</li><li>max: 29 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 16.8 tokens</li><li>max: 29 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task360spolinyesandresponsegeneration

—Dataset: task360spolinyesandresponsegeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 22.68 tokens</li><li>max: 89 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 21.02 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 20.67 tokens</li><li>max: 67 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task510reddittifutitlesummarization

—Dataset: task510reddittifutitlesummarization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 216.21 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 218.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 221.49 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task511reddittifulongtext_summarization

—Dataset: task511reddittifulongtext_summarization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 29 tokens</li><li>mean: 239.99 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 76 tokens</li><li>mean: 239.55 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 244.85 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task345hybridqaanswer_generation

—Dataset: task345hybridqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 22.24 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 21.66 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 20.97 tokens</li><li>max: 47 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task270csrgcounterfactualcontextgeneration

—Dataset: task270csrgcounterfactualcontextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 63 tokens</li><li>mean: 100.12 tokens</li><li>max: 158 tokens</li></ul> | <ul><li>min: 63 tokens</li><li>mean: 98.52 tokens</li><li>max: 142 tokens</li></ul> | <ul><li>min: 62 tokens</li><li>mean: 100.4 tokens</li><li>max: 141 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task307jeopardyanswergenerationfinal

—Dataset: task307jeopardyanswergenerationfinal
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 15 tokens</li><li>mean: 29.63 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 29.27 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 29.25 tokens</li><li>max: 43 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task001quorefquestion_generation

—Dataset: task001quorefquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 201 tokens</li><li>mean: 255.1 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 99 tokens</li><li>mean: 254.46 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 173 tokens</li><li>mean: 255.11 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task089swapwords_verification

—Dataset: task089swapwords_verification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 12.91 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 12.67 tokens</li><li>max: 24 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 12.26 tokens</li><li>max: 22 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1196atomicclassification_oeffect

—Dataset: task1196atomicclassification_oeffect
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 18.77 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 18.57 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 18.5 tokens</li><li>max: 29 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task080piqaanswer_generation

—Dataset: task080piqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 10.89 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 10.71 tokens</li><li>max: 24 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 10.16 tokens</li><li>max: 26 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1598nyclongtextgeneration

—Dataset: task1598nyclongtextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 35.48 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 35.6 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 36.56 tokens</li><li>max: 55 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task240tweetqaquestion_generation

—Dataset: task240tweetqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 27 tokens</li><li>mean: 51.19 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 50.8 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 51.63 tokens</li><li>max: 95 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task615moviesqaanswer_generation

—Dataset: task615moviesqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 11.44 tokens</li><li>max: 23 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 11.45 tokens</li><li>max: 19 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 11.41 tokens</li><li>max: 22 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1347gluests-bsimilarityclassification

—Dataset: task1347gluests-bsimilarityclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 17 tokens</li><li>mean: 31.16 tokens</li><li>max: 88 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 31.12 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 31.04 tokens</li><li>max: 92 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task114isthegivenword_longest

—Dataset: task114isthegivenword_longest
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 25 tokens</li><li>mean: 28.95 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 28.46 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 28.75 tokens</li><li>max: 47 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task292storycommonsensecharactertextgeneration

—Dataset: task292storycommonsensecharactertextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 43 tokens</li><li>mean: 68.1 tokens</li><li>max: 98 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 67.4 tokens</li><li>max: 104 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 69.04 tokens</li><li>max: 96 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task115helpadvice_classification

—Dataset: task115helpadvice_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 2 tokens</li><li>mean: 19.9 tokens</li><li>max: 91 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 18.14 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 19.28 tokens</li><li>max: 137 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task431sentevalobject_count

—Dataset: task431sentevalobject_count
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 16.75 tokens</li><li>max: 37 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.14 tokens</li><li>max: 36 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.78 tokens</li><li>max: 35 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1360numersensemultiplechoiceqageneration

—Dataset: task1360numersensemultiplechoiceqageneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 32 tokens</li><li>mean: 40.58 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>min: 32 tokens</li><li>mean: 40.28 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 32 tokens</li><li>mean: 40.2 tokens</li><li>max: 60 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task177para-nmtparaphrasing

—Dataset: task177para-nmtparaphrasing
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 19.73 tokens</li><li>max: 59 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 18.88 tokens</li><li>max: 58 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 18.29 tokens</li><li>max: 36 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task132daistext_modification

—Dataset: task132daistext_modification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 9.3 tokens</li><li>max: 15 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.1 tokens</li><li>max: 15 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.14 tokens</li><li>max: 15 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task269csrgcounterfactualstorygeneration

—Dataset: task269csrgcounterfactualstorygeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 49 tokens</li><li>mean: 79.75 tokens</li><li>max: 111 tokens</li></ul> | <ul><li>min: 53 tokens</li><li>mean: 79.41 tokens</li><li>max: 116 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 79.46 tokens</li><li>max: 114 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task233iirclinkexistsclassification

—Dataset: task233iirclinkexistsclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 145 tokens</li><li>mean: 235.19 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 142 tokens</li><li>mean: 233.32 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 151 tokens</li><li>mean: 234.78 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task161countwordscontainingletter

—Dataset: task161countwordscontainingletter
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 27 tokens</li><li>mean: 31.0 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 30.83 tokens</li><li>max: 61 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 30.52 tokens</li><li>max: 42 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1205atomicclassification_isafter

—Dataset: task1205atomicclassification_isafter
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 20.94 tokens</li><li>max: 37 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 20.64 tokens</li><li>max: 35 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 21.51 tokens</li><li>max: 37 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task571recipenlgnergeneration

—Dataset: task571recipenlgnergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 117.62 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 117.51 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 109.25 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1292yelpreviewfulltext_categorization

—Dataset: task1292yelpreviewfulltext_categorization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 135.37 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 144.75 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 145.27 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task428sentevalinversion

—Dataset: task428sentevalinversion
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 16.59 tokens</li><li>max: 32 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 14.63 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.31 tokens</li><li>max: 34 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task311racequestion_generation

—Dataset: task311racequestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 115 tokens</li><li>mean: 254.55 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 137 tokens</li><li>mean: 254.56 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 171 tokens</li><li>mean: 255.54 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task429sentevaltense

—Dataset: task429sentevaltense
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 15.9 tokens</li><li>max: 37 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 14.12 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.33 tokens</li><li>max: 36 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task403creakcommonsense_inference

—Dataset: task403creakcommonsense_inference
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 30.04 tokens</li><li>max: 104 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 29.3 tokens</li><li>max: 108 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 29.47 tokens</li><li>max: 122 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task929productsreviews_classification

—Dataset: task929productsreviews_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 69.18 tokens</li><li>max: 126 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 70.54 tokens</li><li>max: 123 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 70.28 tokens</li><li>max: 123 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task582naturalquestionanswer_generation

—Dataset: task582naturalquestionanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 11.69 tokens</li><li>max: 25 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 11.64 tokens</li><li>max: 24 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 11.72 tokens</li><li>max: 25 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task237iircanswerfromsubtextanswergeneration

—Dataset: task237iircanswerfromsubtextanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 22 tokens</li><li>mean: 66.47 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 64.67 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 61.4 tokens</li><li>max: 161 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task050multircanswerability

—Dataset: task050multircanswerability
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 15 tokens</li><li>mean: 32.35 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 31.51 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 32.03 tokens</li><li>max: 159 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task184breakgenerate_question

—Dataset: task184breakgenerate_question
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 39.76 tokens</li><li>max: 147 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 38.97 tokens</li><li>max: 149 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 39.62 tokens</li><li>max: 148 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task669ambigqaanswer_generation

—Dataset: task669ambigqaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 12.91 tokens</li><li>max: 23 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 12.88 tokens</li><li>max: 27 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 12.72 tokens</li><li>max: 22 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task169strategyqasentence_generation

—Dataset: task169strategyqasentence_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 19 tokens</li><li>mean: 35.3 tokens</li><li>max: 65 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 34.36 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 33.36 tokens</li><li>max: 65 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task500scruplesanecdotestitlegeneration

—Dataset: task500scruplesanecdotestitlegeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 224.51 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 232.39 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 234.4 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task241tweetqaclassification

—Dataset: task241tweetqaclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 31 tokens</li><li>mean: 61.75 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 61.98 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 61.67 tokens</li><li>max: 92 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1345glueqqpquestionparaprashing

—Dataset: task1345glueqqpquestionparaprashing
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 16.62 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 15.77 tokens</li><li>max: 69 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 16.61 tokens</li><li>max: 51 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task218rocstoriesswaporderanswer_generation

—Dataset: task218rocstoriesswaporderanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 48 tokens</li><li>mean: 72.42 tokens</li><li>max: 118 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 72.62 tokens</li><li>max: 102 tokens</li></ul> | <ul><li>min: 47 tokens</li><li>mean: 72.14 tokens</li><li>max: 106 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task613politifacttext_generation

—Dataset: task613politifacttext_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 24.71 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 23.58 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 22.87 tokens</li><li>max: 61 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1167penntreebankcoarsepos_tagging

—Dataset: task1167penntreebankcoarsepos_tagging
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 53.81 tokens</li><li>max: 200 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 53.49 tokens</li><li>max: 220 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 54.95 tokens</li><li>max: 202 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1422mathqaphysics

—Dataset: task1422mathqaphysics
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 34 tokens</li><li>mean: 72.14 tokens</li><li>max: 164 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 71.53 tokens</li><li>max: 157 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 72.08 tokens</li><li>max: 155 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task247dreamanswer_generation

—Dataset: task247dreamanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 38 tokens</li><li>mean: 159.4 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 157.79 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 41 tokens</li><li>mean: 167.32 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task199mnliclassification

—Dataset: task199mnliclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 13 tokens</li><li>mean: 43.33 tokens</li><li>max: 127 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 44.68 tokens</li><li>max: 149 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 44.31 tokens</li><li>max: 113 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task164mcscriptquestionansweringtext

—Dataset: task164mcscriptquestionansweringtext
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 150 tokens</li><li>mean: 200.67 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 150 tokens</li><li>mean: 200.46 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 142 tokens</li><li>mean: 200.89 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1541agnewsclassification

—Dataset: task1541agnewsclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 21 tokens</li><li>mean: 53.39 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 52.89 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 53.84 tokens</li><li>max: 161 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task516sentevalconjoints_inversion

—Dataset: task516sentevalconjoints_inversion
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 20.31 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 18.97 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 18.91 tokens</li><li>max: 34 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task294storycommonsensemotivtextgeneration

—Dataset: task294storycommonsensemotivtextgeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 40.09 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 40.44 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 39.58 tokens</li><li>max: 86 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task501scruplesanecdotesposttype_verification

—Dataset: task501scruplesanecdotesposttype_verification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 231.44 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 235.23 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 234.84 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task213rocstoriescorrectendingclassification

—Dataset: task213rocstoriescorrectendingclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 62 tokens</li><li>mean: 86.03 tokens</li><li>max: 125 tokens</li></ul> | <ul><li>min: 60 tokens</li><li>mean: 85.66 tokens</li><li>max: 131 tokens</li></ul> | <ul><li>min: 59 tokens</li><li>mean: 86.01 tokens</li><li>max: 131 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task821protoqaquestion_generation

—Dataset: task821protoqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 14.61 tokens</li><li>max: 61 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 14.97 tokens</li><li>max: 35 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 13.79 tokens</li><li>max: 93 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task493reviewpolarity_classification

—Dataset: task493reviewpolarity_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 18 tokens</li><li>mean: 99.85 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 104.97 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 112.97 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task308jeopardyanswergenerationall

—Dataset: task308jeopardyanswergenerationall
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 27.97 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 27.0 tokens</li><li>max: 44 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 27.52 tokens</li><li>max: 48 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1595event2mindtextgeneration1

—Dataset: task1595event2mindtextgeneration1
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 9.9 tokens</li><li>max: 18 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.96 tokens</li><li>max: 20 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.03 tokens</li><li>max: 20 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task040qascquestion_generation

—Dataset: task040qascquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 15.03 tokens</li><li>max: 29 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.04 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 13.79 tokens</li><li>max: 32 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task231iirclink_classification

—Dataset: task231iirclink_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 179 tokens</li><li>mean: 246.14 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 170 tokens</li><li>mean: 246.33 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 161 tokens</li><li>mean: 246.99 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1727wiqawhatisthe_effect

—Dataset: task1727wiqawhatisthe_effect
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 44 tokens</li><li>mean: 95.04 tokens</li><li>max: 183 tokens</li></ul> | <ul><li>min: 44 tokens</li><li>mean: 95.1 tokens</li><li>max: 185 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 95.37 tokens</li><li>max: 183 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task578curiositydialogsanswergeneration

—Dataset: task578curiositydialogsanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 10 tokens</li><li>mean: 230.36 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 118 tokens</li><li>mean: 235.58 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 229.92 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task310raceclassification

—Dataset: task310raceclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 101 tokens</li><li>mean: 254.92 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 218 tokens</li><li>mean: 255.81 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 101 tokens</li><li>mean: 254.92 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task309raceanswer_generation

—Dataset: task309raceanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 75 tokens</li><li>mean: 254.76 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 204 tokens</li><li>mean: 255.48 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 75 tokens</li><li>mean: 255.23 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task379agnewstopic_classification

—Dataset: task379agnewstopic_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 20 tokens</li><li>mean: 54.44 tokens</li><li>max: 193 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 54.58 tokens</li><li>max: 175 tokens</li></ul> | <ul><li>min: 21 tokens</li><li>mean: 55.12 tokens</li><li>max: 187 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task030winograndefull_person

—Dataset: task030winograndefull_person
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 7 tokens</li><li>mean: 7.63 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 7.52 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 7.39 tokens</li><li>max: 11 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1540parsedpdfs_summarization

—Dataset: task1540parsedpdfs_summarization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 188.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 189.34 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 192.03 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task039qascfindoverlappingwords

—Dataset: task039qascfindoverlappingwords
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 16 tokens</li><li>mean: 30.57 tokens</li><li>max: 55 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 30.03 tokens</li><li>max: 57 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 30.68 tokens</li><li>max: 60 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1206atomicclassification_isbefore

—Dataset: task1206atomicclassification_isbefore
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 21.27 tokens</li><li>max: 40 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 20.85 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 21.37 tokens</li><li>max: 31 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task157countvowelsandconsonants

—Dataset: task157countvowelsandconsonants
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 24 tokens</li><li>mean: 27.98 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 27.87 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 28.32 tokens</li><li>max: 39 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task339recordanswer_generation

—Dataset: task339recordanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 171 tokens</li><li>mean: 234.55 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 171 tokens</li><li>mean: 233.87 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 171 tokens</li><li>mean: 232.63 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task453swaganswer_generation

—Dataset: task453swaganswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 9 tokens</li><li>mean: 18.38 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 18.13 tokens</li><li>max: 63 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 17.47 tokens</li><li>max: 55 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task848pubmedqaclassification

—Dataset: task848pubmedqaclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 21 tokens</li><li>mean: 249.24 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 21 tokens</li><li>mean: 249.85 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 84 tokens</li><li>mean: 251.72 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task673googlewellformedqueryclassification

—Dataset: task673googlewellformedqueryclassification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 11.6 tokens</li><li>max: 27 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 11.2 tokens</li><li>max: 24 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 11.37 tokens</li><li>max: 22 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task676ollierelationshipanswergeneration

—Dataset: task676ollierelationshipanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 29 tokens</li><li>mean: 50.98 tokens</li><li>max: 113 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 48.82 tokens</li><li>max: 134 tokens</li></ul> | <ul><li>min: 30 tokens</li><li>mean: 51.69 tokens</li><li>max: 113 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task268caseholdlegalanswergeneration

—Dataset: task268caseholdlegalanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 235 tokens</li><li>mean: 255.94 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 156 tokens</li><li>mean: 255.5 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 226 tokens</li><li>mean: 255.95 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task844financialphrasebank_classification

—Dataset: task844financialphrasebank_classification
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 14 tokens</li><li>mean: 40.06 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 38.31 tokens</li><li>max: 78 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 38.91 tokens</li><li>max: 86 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task330gapanswer_generation

—Dataset: task330gapanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 26 tokens</li><li>mean: 107.15 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 44 tokens</li><li>mean: 108.5 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 45 tokens</li><li>mean: 111.29 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task595mochaanswer_generation

—Dataset: task595mochaanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 44 tokens</li><li>mean: 94.29 tokens</li><li>max: 178 tokens</li></ul> | <ul><li>min: 21 tokens</li><li>mean: 95.79 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 117.82 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task1285kpakeypoint_matching

—Dataset: task1285kpakeypoint_matching
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 30 tokens</li><li>mean: 52.19 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 50.09 tokens</li><li>max: 84 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 53.0 tokens</li><li>max: 88 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task234iircpassagelineanswer_generation

—Dataset: task234iircpassagelineanswer_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 143 tokens</li><li>mean: 234.48 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 155 tokens</li><li>mean: 235.32 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 146 tokens</li><li>mean: 236.21 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task494reviewpolarityanswergeneration

—Dataset: task494reviewpolarityanswergeneration
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 107.59 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 114.18 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 114.95 tokens</li><li>max: 249 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task670ambigqaquestion_generation

—Dataset: task670ambigqaquestion_generation
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 11 tokens</li><li>mean: 12.7 tokens</li><li>max: 26 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 12.46 tokens</li><li>max: 23 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 12.24 tokens</li><li>max: 18 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

task289gigawordsummarization

—Dataset: task289gigawordsummarization
—Size: 634 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 634 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 25 tokens</li><li>mean: 51.28 tokens</li><li>max: 87 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 51.71 tokens</li><li>max: 87 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 51.14 tokens</li><li>max: 87 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

npr

—Dataset: npr
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 12.18 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 146.68 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 109.65 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

nli

—Dataset: nli
—Size: 49,548 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 21.0 tokens</li><li>max: 229 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 11.74 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 11.98 tokens</li><li>max: 45 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

SimpleWiki

—Dataset: SimpleWiki
—Size: 5,006 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 29.27 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 33.55 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 55.34 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

amazonreview2018

—Dataset: amazonreview2018
—Size: 99,032 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 11.29 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 87.93 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 69.37 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

ccnewstitletext

—Dataset: ccnewstitletext
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 15.71 tokens</li><li>max: 57 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 209.36 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 21 tokens</li><li>mean: 197.52 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

agnews

—Dataset: agnews
—Size: 44,606 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 11.84 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 40.9 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 44.47 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

xsum

—Dataset: xsum
—Size: 9,948 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 8 tokens</li><li>mean: 27.96 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 227.43 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 229.78 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

msmarco

—Dataset: msmarco
—Size: 173,290 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 9.09 tokens</li><li>max: 39 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 82.25 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 79.69 tokens</li><li>max: 220 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

yahooanswerstitle_answer

—Dataset: yahooanswerstitle_answer
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 16.8 tokens</li><li>max: 69 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 78.53 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 87.35 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

squad_pairs

—Dataset: squad_pairs
—Size: 24,774 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 14.48 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 152.39 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 160.54 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

wow

—Dataset: wow
—Size: 29,716 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 90.07 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 111.81 tokens</li><li>max: 150 tokens</li></ul> | <ul><li>min: 92 tokens</li><li>mean: 113.15 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-amazoncounterfactual-avstriplets

—Dataset: mteb-amazoncounterfactual-avstriplets
—Size: 3,991 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 12 tokens</li><li>mean: 27.26 tokens</li><li>max: 137 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 26.57 tokens</li><li>max: 96 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 26.88 tokens</li><li>max: 96 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-amazonmassiveintent-avs_triplets

—Dataset: mteb-amazonmassiveintent-avs_triplets
—Size: 11,405 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 9.49 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 9.19 tokens</li><li>max: 32 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 9.49 tokens</li><li>max: 25 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-amazonmassivescenario-avs_triplets

—Dataset: mteb-amazonmassivescenario-avs_triplets
—Size: 11,405 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 9.59 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 8.97 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 9.69 tokens</li><li>max: 29 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-amazonreviewsmulti-avs_triplets

—Dataset: mteb-amazonreviewsmulti-avs_triplets
—Size: 198,000 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 49.83 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 51.32 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 49.66 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-banking77-avs_triplets

—Dataset: mteb-banking77-avs_triplets
—Size: 9,947 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 16.19 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 15.76 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 15.78 tokens</li><li>max: 87 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-emotion-avs_triplets

—Dataset: mteb-emotion-avs_triplets
—Size: 15,840 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 21.76 tokens</li><li>max: 65 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 17.13 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 21.95 tokens</li><li>max: 65 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-imdb-avs_triplets

—Dataset: mteb-imdb-avs_triplets
—Size: 24,647 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 34 tokens</li><li>mean: 207.65 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 57 tokens</li><li>mean: 222.57 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 207.98 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-mtopdomain-avstriplets

—Dataset: mteb-mtopdomain-avstriplets
—Size: 15,523 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 10.29 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 9.7 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 10.01 tokens</li><li>max: 28 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-mtopintent-avstriplets

—Dataset: mteb-mtopintent-avstriplets
—Size: 15,523 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 4 tokens</li><li>mean: 10.11 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 9.64 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 10.13 tokens</li><li>max: 33 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-toxicconversations50k-avs_triplets

—Dataset: mteb-toxicconversations50k-avs_triplets
—Size: 49,421 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 68.39 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 91.3 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 70.1 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

mteb-tweetsentimentextraction-avs_triplets

—Dataset: mteb-tweetsentimentextraction-avs_triplets
—Size: 27,245 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 3 tokens</li><li>mean: 20.32 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 20.24 tokens</li><li>max: 51 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 20.98 tokens</li><li>max: 51 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

covid-bing-query-gpt4-avs_triplets

—Dataset: covid-bing-query-gpt4-avs_triplets
—Size: 4,942 training samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 6 tokens</li><li>mean: 15.22 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 37.46 tokens</li><li>max: 167 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 37.77 tokens</li><li>max: 128 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

Evaluation Dataset

Unnamed Dataset

—Size: 18,269 evaluation samples
—Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
—Approximate statistics based on the first 1000 samples: | | anchor | positive | negative | |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | string | | details | <ul><li>min: 5 tokens</li><li>mean: 15.5 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 143.45 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 145.01 tokens</li><li>max: 256 tokens</li></ul> |
—Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

json

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

Training Hyperparameters

Non-Default Hyperparameters

—eval_strategy: steps
—per_device_train_batch_size: 64
—per_device_eval_batch_size: 64
—learning_rate: 2e-05
—num_train_epochs: 10
—warmup_ratio: 0.1
—fp16: True
—gradient_checkpointing: True
—batch_sampler: no_duplicates

All Hyperparameters

<details><summary>Click to expand</summary>

—overwrite_output_dir: False
—do_predict: False
—eval_strategy: steps
—prediction_loss_only: True
—per_device_train_batch_size: 64
—per_device_eval_batch_size: 64
—per_gpu_train_batch_size: None
—per_gpu_eval_batch_size: None
—gradient_accumulation_steps: 1
—eval_accumulation_steps: None
—torch_empty_cache_steps: None
—learning_rate: 2e-05
—weight_decay: 0.0
—adam_beta1: 0.9
—adam_beta2: 0.999
—adam_epsilon: 1e-08
—max_grad_norm: 1.0
—num_train_epochs: 10
—max_steps: -1
—lr_scheduler_type: linear
—lr_scheduler_kwargs: {}
—warmup_ratio: 0.1
—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
—restore_callback_states_from_checkpoint: 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: True
—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: {'minnumparams': 0, 'xla': False, 'xlafsdpv2': False, 'xlafsdpgrad_ckpt': False}
—fsdp_transformer_layer_cls_to_wrap: None
—accelerator_config: {'splitbatches': False, 'dispatchbatches': None, 'evenbatches': True, 'useseedablesampler': True, 'nonblocking': False, 'gradientaccumulationkwargs': 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: True
—gradient_checkpointing_kwargs: None
—include_inputs_for_metrics: False
—include_for_metrics: []
—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_eval_metrics: False
—eval_on_start: False
—use_liger_kernel: False
—eval_use_gather_object: False
—average_tokens_across_devices: False
—prompts: None
—batch_sampler: no_duplicates
—multi_dataset_batch_sampler: proportional

</details>

Training Logs

<details><summary>Click to expand</summary>

Epoch	Step	Training Loss	Validation Loss	medi-mteb-dev_cosine_accuracy
0	0	-	-	0.8503
0.0175	500	1.9411	1.9039	0.8588
0.0351	1000	1.5495	0.9698	0.8698
0.0526	1500	1.3527	0.7684	0.8753
0.0701	2000	1.1995	0.7102	0.8777
0.0877	2500	1.1782	0.6829	0.8793
0.1052	3000	1.1662	0.6633	0.8830
0.1227	3500	1.139	0.6510	0.8844
0.1403	4000	1.1389	0.6429	0.8851
0.1578	4500	1.1381	0.6273	0.8863
0.1753	5000	1.0616	0.6225	0.8869
0.1929	5500	1.114	0.6169	0.8872
0.2104	6000	0.9854	0.6108	0.8886
0.2279	6500	1.081	0.6047	0.8900
0.2455	7000	0.9899	0.5983	0.8912
0.2630	7500	1.0551	0.5931	0.8921
0.2805	8000	1.0515	0.5882	0.8930
0.2981	8500	1.0384	0.5768	0.8946
0.3156	9000	1.0545	0.5716	0.8945
0.3331	9500	1.006	0.5744	0.8959
0.3507	10000	0.9629	0.5719	0.8960
0.3682	10500	1.0877	0.5600	0.8958
0.3857	11000	1.0594	0.5639	0.8975
0.4033	11500	1.0708	0.5672	0.8975
0.4208	12000	1.0275	0.5481	0.8986
0.4383	12500	0.9467	0.5552	0.9007
0.4559	13000	1.0048	0.5524	0.9008
0.4734	13500	1.0135	0.5482	0.9002
0.4909	14000	0.9579	0.5428	0.9002
0.5085	14500	0.9534	0.5373	0.9015
0.5260	15000	0.9225	0.5347	0.9025
0.5435	15500	0.9936	0.5384	0.9011
0.5611	16000	0.926	0.5298	0.9028
0.5786	16500	0.9904	0.5338	0.9034
0.5961	17000	0.9302	0.5281	0.9033
0.6137	17500	0.908	0.5332	0.9025
0.6312	18000	0.8936	0.5322	0.9046
0.6487	18500	0.9549	0.5312	0.9039
0.6663	19000	0.9498	0.5319	0.9030
0.6838	19500	0.9291	0.5279	0.9038
0.7013	20000	0.9573	0.5165	0.9017
0.7189	20500	0.9395	0.5223	0.9039
0.7364	21000	0.8753	0.5335	0.9009
0.7539	21500	0.95	0.5173	0.9040
0.7715	22000	0.9656	0.5451	0.9043
0.7890	22500	0.9145	0.5305	0.9033
0.8065	23000	0.9768	0.5135	0.9041
0.8241	23500	0.8779	0.5185	0.9037
0.8416	24000	0.9603	0.5338	0.9036
0.8591	24500	0.9045	0.5090	0.9056
0.8767	25000	0.9536	0.5254	0.9043
0.8942	25500	0.8499	0.5388	0.9023
0.9117	26000	0.88	0.5676	0.9011
0.9293	26500	0.8884	0.5127	0.9046
0.9468	27000	0.8556	0.5227	0.9065
0.9643	27500	0.8641	0.5901	0.9027
0.9819	28000	0.8884	0.4982	0.9054
0.9994	28500	0.8404	0.5078	0.9064
1.0169	29000	0.8613	0.5211	0.9052
1.0345	29500	0.8971	0.5061	0.9065
1.0520	30000	0.9426	0.5118	0.9062
1.0695	30500	0.8791	0.5062	0.9062
1.0871	31000	0.8953	0.5056	0.9044
1.1046	31500	0.9229	0.5002	0.9065
1.1221	32000	0.8914	0.4912	0.9088
1.1397	32500	0.9105	0.4973	0.9086
1.1572	33000	0.9168	0.4954	0.9074
1.1747	33500	0.845	0.5073	0.9088
1.1923	34000	0.9209	0.4890	0.9088
1.2098	34500	0.8014	0.5063	0.9063
1.2273	35000	0.8888	0.5270	0.9070
1.2449	35500	0.8269	0.5062	0.9059
1.2624	36000	0.8637	0.4951	0.9054
1.2799	36500	0.8796	0.4922	0.9083
1.2975	37000	0.8644	0.4851	0.9068
1.3150	37500	0.8907	0.5396	0.9069
1.3325	38000	0.8477	0.4944	0.9082
1.3501	38500	0.8237	0.4915	0.9081
1.3676	39000	0.9217	0.4918	0.9083
1.3851	39500	0.887	0.4955	0.9064
1.4027	40000	0.9172	0.5259	0.9077
1.4202	40500	0.8693	0.5002	0.9092
1.4377	41000	0.8223	0.5109	0.9084
1.4553	41500	0.8554	0.4859	0.9079
1.4728	42000	0.8772	0.4850	0.9079
1.4903	42500	0.8232	0.4860	0.9088
1.5079	43000	0.8218	0.4917	0.9083
1.5254	43500	0.7905	0.4839	0.9094
1.5429	44000	0.847	0.5150	0.9081
1.5605	44500	0.7929	0.5234	0.9082
1.5780	45000	0.8621	0.5084	0.9094
1.5955	45500	0.7908	0.4980	0.9092
1.6131	46000	0.792	0.5385	0.9071
1.6306	46500	0.7569	0.5405	0.9088
1.6481	47000	0.8178	0.5172	0.9078
1.6657	47500	0.8101	0.5379	0.9082
1.6832	48000	0.8013	0.5627	0.9068
1.7007	48500	0.8298	0.5947	0.9072
1.7183	49000	0.8028	0.5302	0.9076
1.7358	49500	0.7663	0.5523	0.9066
1.7533	50000	0.8255	0.5361	0.9080
1.7709	50500	0.8354	0.5373	0.9080
1.7884	51000	0.7917	0.5546	0.9079
1.8059	51500	0.837	0.5113	0.9085
1.8235	52000	0.7488	0.5037	0.9082
1.8410	52500	0.8439	0.5349	0.9084
1.8585	53000	0.7688	0.5279	0.9083
1.8761	53500	0.8205	0.5496	0.9071
1.8936	54000	0.7256	0.5454	0.9075
1.9111	54500	0.7536	0.5582	0.9060
1.9287	55000	0.7544	0.5331	0.9075
1.9462	55500	0.7332	0.5139	0.9091
1.9637	56000	0.7244	0.5767	0.9078
1.9813	56500	0.7574	0.4962	0.9084
1.9988	57000	0.7116	0.5210	0.9090
2.0163	57500	0.7376	0.5196	0.9088
2.0339	58000	0.768	0.5609	0.9086
2.0514	58500	0.8056	0.5230	0.9081
2.0689	59000	0.7744	0.5527	0.9077
2.0865	59500	0.7543	0.4949	0.9090
2.1040	60000	0.8	0.4925	0.9095
2.1215	60500	0.7664	0.4989	0.9093
2.1391	61000	0.7849	0.4956	0.9106
2.1566	61500	0.7955	0.5312	0.9099
2.1741	62000	0.7326	0.5126	0.9112
2.1917	62500	0.7975	0.4701	0.9114
2.2092	63000	0.7001	0.5118	0.9093
2.2267	63500	0.7477	0.5371	0.9102
2.2443	64000	0.7227	0.5536	0.9083
2.2618	64500	0.7687	0.5174	0.9102
2.2793	65000	0.7633	0.4925	0.9102
2.2969	65500	0.7572	0.5059	0.9093
2.3144	66000	0.7846	0.5391	0.9088
2.3319	66500	0.7434	0.4991	0.9111
2.3495	67000	0.7124	0.5115	0.9107
2.3670	67500	0.8085	0.4974	0.9086
2.3845	68000	0.7879	0.5114	0.9089
2.4021	68500	0.7977	0.5297	0.9086
2.4196	69000	0.782	0.5251	0.9103
2.4371	69500	0.7237	0.5568	0.9088
2.4547	70000	0.7556	0.5008	0.9098
2.4722	70500	0.777	0.4784	0.9097
2.4897	71000	0.7205	0.4993	0.9097
2.5073	71500	0.7237	0.5096	0.9102
2.5248	72000	0.6976	0.4833	0.9107
2.5423	72500	0.7572	0.5234	0.9092
2.5599	73000	0.7012	0.5339	0.9096
2.5774	73500	0.7799	0.5056	0.9107
2.5949	74000	0.7036	0.4961	0.9101
2.6125	74500	0.6932	0.5656	0.9088
2.6300	75000	0.6676	0.5347	0.9097
2.6475	75500	0.7246	0.5110	0.9101
2.6651	76000	0.715	0.5551	0.9096
2.6826	76500	0.7298	0.5658	0.9106
2.7001	77000	0.7349	0.5571	0.9106
2.7177	77500	0.721	0.5667	0.9100
2.7352	78000	0.6863	0.5616	0.9066
2.7527	78500	0.739	0.5419	0.9101
2.7703	79000	0.7529	0.5343	0.9107
2.7878	79500	0.7008	0.5601	0.9107
2.8053	80000	0.7655	0.5189	0.9097
2.8229	80500	0.6666	0.5073	0.9106
2.8404	81000	0.7551	0.5381	0.9102
2.8579	81500	0.6769	0.5650	0.9092
2.8755	82000	0.7508	0.5189	0.9097
2.8930	82500	0.6418	0.5521	0.9094
2.9105	83000	0.6808	0.5490	0.9095
2.9281	83500	0.6833	0.5524	0.9092
2.9456	84000	0.6508	0.5229	0.9105
2.9631	84500	0.6576	0.5789	0.9100
2.9807	85000	0.6778	0.5075	0.9108
2.9982	85500	0.642	0.5139	0.9107
3.0157	86000	0.6596	0.5337	0.9104
3.0333	86500	0.6769	0.5713	0.9106
3.0508	87000	0.7349	0.5374	0.9103
3.0683	87500	0.7034	0.5680	0.9094
3.0859	88000	0.6853	0.5130	0.9106
3.1034	88500	0.726	0.5093	0.9123
3.1209	89000	0.6939	0.5078	0.9104
3.1385	89500	0.7085	0.4847	0.9125
3.1560	90000	0.7118	0.5154	0.9113
3.1735	90500	0.6755	0.5066	0.9121
3.1911	91000	0.718	0.4665	0.9129
3.2086	91500	0.6277	0.5047	0.9111
3.2261	92000	0.6907	0.5292	0.9123
3.2437	92500	0.6624	0.5414	0.9103
3.2612	93000	0.6943	0.5274	0.9101
3.2787	93500	0.6979	0.4985	0.9110
3.2963	94000	0.6858	0.5156	0.9099
3.3138	94500	0.7221	0.5062	0.9114
3.3313	95000	0.6647	0.5129	0.9108
3.3489	95500	0.6572	0.5213	0.9127
3.3664	96000	0.7417	0.4926	0.9119
3.3839	96500	0.7237	0.5090	0.9104
3.4015	97000	0.7218	0.5336	0.9111
3.4190	97500	0.7091	0.5062	0.9128
3.4365	98000	0.668	0.5727	0.9118
3.4541	98500	0.6724	0.5106	0.9119
3.4716	99000	0.7331	0.4740	0.9130
3.4891	99500	0.6427	0.5021	0.9119
3.5067	100000	0.6659	0.5037	0.9119
3.5242	100500	0.6413	0.5024	0.9109
3.5417	101000	0.6889	0.5277	0.9109
3.5593	101500	0.6401	0.5389	0.9103
3.5768	102000	0.7116	0.5114	0.9111
3.5943	102500	0.6511	0.5124	0.9112
3.6119	103000	0.6392	0.5505	0.9096
3.6294	103500	0.6049	0.5306	0.9099
3.6469	104000	0.675	0.5219	0.9098
3.6645	104500	0.6498	0.5392	0.9100
3.6820	105000	0.6774	0.5609	0.9097
3.6995	105500	0.6655	0.5441	0.9107
3.7171	106000	0.6664	0.5713	0.9113
3.7346	106500	0.6343	0.5742	0.9086
3.7521	107000	0.6686	0.5225	0.9113
3.7697	107500	0.7018	0.5221	0.9111
3.7872	108000	0.6479	0.5641	0.9113
3.8047	108500	0.7005	0.5352	0.9123
3.8223	109000	0.6068	0.5007	0.9107
3.8398	109500	0.6846	0.5593	0.9102
3.8573	110000	0.6272	0.5458	0.9107
3.8749	110500	0.685	0.5178	0.9100
3.8924	111000	0.5992	0.5200	0.9102
3.9099	111500	0.6231	0.5488	0.9101
3.9275	112000	0.6343	0.5496	0.9100
3.9450	112500	0.593	0.5207	0.9115
3.9625	113000	0.6017	0.5679	0.9108
3.9801	113500	0.6218	0.5174	0.9113
3.9976	114000	0.5916	0.5108	0.9118
4.0151	114500	0.603	0.5259	0.9117
4.0327	115000	0.6215	0.5362	0.9121
4.0502	115500	0.6784	0.5343	0.9112
4.0677	116000	0.65	0.5488	0.9114
4.0853	116500	0.632	0.4905	0.9119
4.1028	117000	0.6708	0.5091	0.9129
4.1203	117500	0.6374	0.5228	0.9124
4.1379	118000	0.6593	0.4976	0.9125
4.1554	118500	0.649	0.5151	0.9109
4.1729	119000	0.629	0.5303	0.9124
4.1905	119500	0.6709	0.4868	0.9121
4.2080	120000	0.5803	0.5177	0.9130
4.2255	120500	0.6356	0.5329	0.9140
4.2431	121000	0.6075	0.5057	0.9129
4.2606	121500	0.6463	0.5084	0.9126
4.2781	122000	0.6408	0.4859	0.9127
4.2957	122500	0.6331	0.5210	0.9114
4.3132	123000	0.6719	0.4893	0.9122
4.3308	123500	0.6227	0.5126	0.9129
4.3483	124000	0.6144	0.5293	0.9136
4.3658	124500	0.6589	0.4978	0.9127
4.3834	125000	0.6849	0.5195	0.9122
4.4009	125500	0.6731	0.5150	0.9119
4.4184	126000	0.658	0.4890	0.9136
4.4360	126500	0.6256	0.5271	0.9134
4.4535	127000	0.6295	0.5182	0.9129
4.4710	127500	0.6804	0.4870	0.9133
4.4886	128000	0.5868	0.4831	0.9129
4.5061	128500	0.6316	0.4963	0.9135
4.5236	129000	0.5873	0.5179	0.9149
4.5412	129500	0.6383	0.5188	0.9126
4.5587	130000	0.5936	0.5420	0.9117
4.5762	130500	0.654	0.5248	0.9123
4.5938	131000	0.6172	0.5067	0.9130
4.6113	131500	0.5766	0.5335	0.9117
4.6288	132000	0.5688	0.5345	0.9106
4.6464	132500	0.6254	0.5352	0.9115
4.6639	133000	0.5978	0.5244	0.9117
4.6814	133500	0.6332	0.5511	0.9119
4.6990	134000	0.6209	0.5356	0.9120
4.7165	134500	0.6166	0.5532	0.9125
4.7340	135000	0.5897	0.5888	0.9105
4.7516	135500	0.624	0.5153	0.9123
4.7691	136000	0.6563	0.5260	0.9134
4.7866	136500	0.6098	0.5603	0.9122
4.8042	137000	0.6313	0.5390	0.9124
4.8217	137500	0.5737	0.5093	0.9129
4.8392	138000	0.6475	0.5320	0.9114
4.8568	138500	0.5752	0.5531	0.9120
4.8743	139000	0.6378	0.4997	0.9114
4.8918	139500	0.5641	0.5121	0.9120
4.9094	140000	0.5771	0.5343	0.9114
4.9269	140500	0.5869	0.5277	0.9124
4.9444	141000	0.5417	0.5105	0.9143
4.9620	141500	0.5517	0.5664	0.9133
4.9795	142000	0.589	0.5326	0.9122
4.9970	142500	0.5449	0.5236	0.9136
5.0146	143000	0.5687	0.5217	0.9141
5.0321	143500	0.5815	0.5520	0.9131
5.0496	144000	0.6309	0.5290	0.9125
5.0672	144500	0.6086	0.5305	0.9128
5.0847	145000	0.5905	0.5044	0.9135
5.1022	145500	0.6242	0.5113	0.9144
5.1198	146000	0.603	0.5263	0.9137
5.1373	146500	0.6187	0.5086	0.9131
5.1548	147000	0.6007	0.5291	0.9136
5.1724	147500	0.5934	0.5113	0.9131
5.1899	148000	0.6208	0.4981	0.9142
5.2074	148500	0.5524	0.5414	0.9146
5.2250	149000	0.5941	0.5274	0.9146
5.2425	149500	0.5694	0.5315	0.9140
5.2600	150000	0.6045	0.5177	0.9138
5.2776	150500	0.5928	0.4923	0.9146
5.2951	151000	0.594	0.5209	0.9138
5.3126	151500	0.6303	0.5014	0.9137
5.3302	152000	0.5867	0.5151	0.9135
5.3477	152500	0.5686	0.5244	0.9142
5.3652	153000	0.6198	0.5063	0.9140
5.3828	153500	0.6458	0.5403	0.9131
5.4003	154000	0.6284	0.4988	0.9140
5.4178	154500	0.6192	0.5008	0.9143
5.4354	155000	0.5943	0.5334	0.9134
5.4529	155500	0.5725	0.5270	0.9141
5.4704	156000	0.656	0.4985	0.9146
5.4880	156500	0.5562	0.4863	0.9137
5.5055	157000	0.5888	0.5099	0.9141
5.5230	157500	0.5329	0.5039	0.9149
5.5406	158000	0.619	0.5232	0.9136
5.5581	158500	0.5528	0.5471	0.9135
5.5756	159000	0.6086	0.5226	0.9125
5.5932	159500	0.5895	0.5072	0.9132
5.6107	160000	0.5358	0.5419	0.9139
5.6282	160500	0.5438	0.5334	0.9121
5.6458	161000	0.579	0.5548	0.9118
5.6633	161500	0.5636	0.5257	0.9127
5.6808	162000	0.5984	0.5520	0.9136
5.6984	162500	0.581	0.5314	0.9135
5.7159	163000	0.5923	0.5665	0.9132
5.7334	163500	0.5433	0.5717	0.9121
5.7510	164000	0.583	0.5338	0.9137
5.7685	164500	0.6272	0.5275	0.9137
5.7860	165000	0.576	0.5657	0.9130
5.8036	165500	0.5983	0.5457	0.9131
5.8211	166000	0.5389	0.5252	0.9141
5.8386	166500	0.6035	0.5478	0.9131
5.8562	167000	0.5398	0.5334	0.9136
5.8737	167500	0.5986	0.5021	0.9136
5.8912	168000	0.5383	0.5261	0.9137
5.9088	168500	0.5376	0.5374	0.9128
5.9263	169000	0.5555	0.5375	0.9136
5.9438	169500	0.5182	0.5230	0.9137
5.9614	170000	0.5175	0.5653	0.9143
5.9789	170500	0.5572	0.5433	0.9141
5.9964	171000	0.5169	0.5035	0.9151
6.0140	171500	0.5336	0.5178	0.9149
6.0315	172000	0.5479	0.5427	0.9141
6.0490	172500	0.5885	0.5417	0.9137
6.0666	173000	0.5694	0.5232	0.9138
6.0841	173500	0.5634	0.5074	0.9142
6.1016	174000	0.5888	0.5102	0.9145
6.1192	174500	0.576	0.5225	0.9148
6.1367	175000	0.5843	0.5161	0.9144
6.1542	175500	0.5635	0.5244	0.9141
6.1718	176000	0.5666	0.5088	0.9149
6.1893	176500	0.5868	0.5185	0.9150
6.2068	177000	0.5211	0.5348	0.9154
6.2244	177500	0.5672	0.5268	0.9150
6.2419	178000	0.5286	0.5431	0.9141
6.2594	178500	0.5723	0.5359	0.9154
6.2770	179000	0.5648	0.5016	0.9154
6.2945	179500	0.5566	0.5200	0.9145
6.3120	180000	0.6074	0.5132	0.9145
6.3296	180500	0.5473	0.5294	0.9145
6.3471	181000	0.5325	0.5380	0.9150
6.3646	181500	0.5868	0.5243	0.9149
6.3822	182000	0.6155	0.5368	0.9143
6.3997	182500	0.5944	0.4978	0.9149
6.4172	183000	0.5838	0.5224	0.9146
6.4348	183500	0.5644	0.5384	0.9146
6.4523	184000	0.5471	0.5549	0.9152
6.4698	184500	0.6198	0.5101	0.9147
6.4874	185000	0.5304	0.5016	0.9152
6.5049	185500	0.5621	0.5076	0.9155
6.5224	186000	0.5027	0.5085	0.9148
6.5400	186500	0.5882	0.5293	0.9147
6.5575	187000	0.5228	0.5374	0.9152
6.5750	187500	0.5717	0.5233	0.9140
6.5926	188000	0.5651	0.5269	0.9136
6.6101	188500	0.5182	0.5328	0.9140
6.6276	189000	0.508	0.5250	0.9134
6.6452	189500	0.5464	0.5427	0.9128
6.6627	190000	0.5362	0.5137	0.9136
6.6802	190500	0.5732	0.5161	0.9148
6.6978	191000	0.5466	0.5416	0.9136
6.7153	191500	0.5501	0.5736	0.9137
6.7328	192000	0.5258	0.5528	0.9130
6.7504	192500	0.5589	0.5380	0.9142
6.7679	193000	0.5947	0.5297	0.9148
6.7854	193500	0.5579	0.5590	0.9145
6.8030	194000	0.5644	0.5412	0.9142
6.8205	194500	0.5128	0.5181	0.9137
6.8380	195000	0.5802	0.5451	0.9136
6.8556	195500	0.5002	0.5293	0.9144
6.8731	196000	0.5763	0.5153	0.9140
6.8906	196500	0.5205	0.5261	0.9144
6.9082	197000	0.5112	0.5342	0.9149
6.9257	197500	0.523	0.5503	0.9140
6.9432	198000	0.4875	0.5420	0.9148
6.9608	198500	0.4963	0.5638	0.9142
6.9783	199000	0.5327	0.5536	0.9149
6.9958	199500	0.4822	0.5224	0.9141
7.0134	200000	0.5078	0.5300	0.9140
7.0309	200500	0.5208	0.5486	0.9149
7.0484	201000	0.5641	0.5442	0.9148
7.0660	201500	0.5484	0.5165	0.9143
7.0835	202000	0.5289	0.5206	0.9142
7.1010	202500	0.557	0.5178	0.9146
7.1186	203000	0.556	0.5190	0.9147
7.1361	203500	0.5567	0.5244	0.9143
7.1536	204000	0.5376	0.5212	0.9148
7.1712	204500	0.5448	0.5138	0.9150
7.1887	205000	0.5541	0.5231	0.9155
7.2062	205500	0.5006	0.5261	0.9155
7.2238	206000	0.5366	0.5184	0.9159
7.2413	206500	0.5127	0.5360	0.9148
7.2588	207000	0.5469	0.5225	0.9148
7.2764	207500	0.5414	0.5080	0.9152
7.2939	208000	0.5361	0.5135	0.9151
7.3114	208500	0.5833	0.5132	0.9147
7.3290	209000	0.515	0.5282	0.9137
7.3465	209500	0.5165	0.5362	0.9154
7.3640	210000	0.5551	0.5327	0.9159
7.3816	210500	0.5845	0.5409	0.9143
7.3991	211000	0.5798	0.5057	0.9147
7.4166	211500	0.5614	0.5275	0.9149
7.4342	212000	0.5445	0.5175	0.9153
7.4517	212500	0.5175	0.5424	0.9139
7.4692	213000	0.6043	0.5075	0.9148
7.4868	213500	0.5051	0.5067	0.9154
7.5043	214000	0.5337	0.5143	0.9153
7.5218	214500	0.4822	0.5049	0.9156
7.5394	215000	0.5722	0.5359	0.9153
7.5569	215500	0.5014	0.5306	0.9147
7.5744	216000	0.5441	0.5222	0.9138
7.5920	216500	0.5391	0.5261	0.9138
7.6095	217000	0.494	0.5275	0.9144
7.6270	217500	0.4881	0.5268	0.9141
7.6446	218000	0.5263	0.5381	0.9138
7.6621	218500	0.5017	0.5209	0.9134
7.6796	219000	0.5566	0.5347	0.9138
7.6972	219500	0.5201	0.5519	0.9135
7.7147	220000	0.5269	0.5718	0.9143
7.7322	220500	0.5125	0.5442	0.9135
7.7498	221000	0.5307	0.5292	0.9142
7.7673	221500	0.5718	0.5179	0.9140
7.7848	222000	0.5345	0.5512	0.9147
7.8024	222500	0.5456	0.5447	0.9143
7.8199	223000	0.4889	0.5197	0.9144
7.8374	223500	0.5532	0.5487	0.9146
7.8550	224000	0.4902	0.5257	0.9137
7.8725	224500	0.5535	0.5095	0.9135
7.8900	225000	0.4988	0.5404	0.9141
7.9076	225500	0.4883	0.5280	0.9143
7.9251	226000	0.4975	0.5458	0.9133
7.9426	226500	0.4698	0.5357	0.9147
7.9602	227000	0.4831	0.5391	0.9143
7.9777	227500	0.5073	0.5492	0.9148
7.9952	228000	0.4637	0.5140	0.9148
8.0128	228500	0.4817	0.5200	0.9137
8.0303	229000	0.5078	0.5370	0.9146
8.0478	229500	0.5342	0.5497	0.9149
8.0654	230000	0.5317	0.5179	0.9156
8.0829	230500	0.5074	0.5286	0.9151
8.1004	231000	0.5302	0.5165	0.9162
8.1180	231500	0.5481	0.5200	0.9163
8.1355	232000	0.538	0.5216	0.9161
8.1530	232500	0.5168	0.5189	0.9152
8.1706	233000	0.5118	0.5195	0.9153
8.1881	233500	0.5394	0.5192	0.9155
8.2056	234000	0.488	0.5100	0.9153
8.2232	234500	0.5214	0.5162	0.9161
8.2407	235000	0.4944	0.5343	0.9149
8.2582	235500	0.5226	0.5190	0.9152
8.2758	236000	0.5234	0.5146	0.9159
8.2933	236500	0.5165	0.5011	0.9153
8.3108	237000	0.5599	0.5129	0.9152
8.3284	237500	0.4991	0.5212	0.9154
8.3459	238000	0.5007	0.5383	0.9148
8.3634	238500	0.5406	0.5394	0.9154
8.3810	239000	0.5606	0.5445	0.9147
8.3985	239500	0.5626	0.5143	0.9149
8.4160	240000	0.5353	0.5338	0.9156
8.4336	240500	0.5168	0.5208	0.9158
8.4511	241000	0.5058	0.5312	0.9146
8.4686	241500	0.5919	0.5143	0.9149
8.4862	242000	0.4883	0.5149	0.9159
8.5037	242500	0.5072	0.5132	0.9156
8.5212	243000	0.4655	0.5111	0.9148
8.5388	243500	0.5592	0.5269	0.9155
8.5563	244000	0.4836	0.5217	0.9152
8.5738	244500	0.5299	0.5269	0.9143
8.5914	245000	0.5081	0.5206	0.9136
8.6089	245500	0.48	0.5159	0.9144
8.6264	246000	0.4713	0.5272	0.9141
8.6440	246500	0.5038	0.5287	0.9139
8.6615	247000	0.4872	0.5199	0.9142
8.6790	247500	0.5429	0.5227	0.9138
8.6966	248000	0.5042	0.5402	0.9136
8.7141	248500	0.511	0.5530	0.9141
8.7316	249000	0.5097	0.5374	0.9131
8.7492	249500	0.4974	0.5312	0.9138
8.7667	250000	0.5617	0.5381	0.9148
8.7842	250500	0.5234	0.5476	0.9150
8.8018	251000	0.5133	0.5447	0.9147
8.8193	251500	0.488	0.5270	0.9148
8.8368	252000	0.5377	0.5325	0.9144
8.8544	252500	0.479	0.5324	0.9145
8.8719	253000	0.5329	0.5200	0.9140
8.8894	253500	0.4744	0.5346	0.9140
8.9070	254000	0.4827	0.5333	0.9145
8.9245	254500	0.4757	0.5415	0.9139
8.9420	255000	0.4504	0.5307	0.9147
8.9596	255500	0.4657	0.5337	0.9146
8.9771	256000	0.4976	0.5473	0.9150
8.9946	256500	0.459	0.5214	0.9144
9.0122	257000	0.4615	0.5296	0.9147
9.0297	257500	0.5019	0.5312	0.9149
9.0472	258000	0.5142	0.5379	0.9152
9.0648	258500	0.5174	0.5197	0.9150
9.0823	259000	0.4896	0.5277	0.9155
9.0998	259500	0.5114	0.5240	0.9161
9.1174	260000	0.529	0.5293	0.9155
9.1349	260500	0.5305	0.5242	0.9157
9.1524	261000	0.4941	0.5160	0.9155
9.1700	261500	0.5025	0.5274	0.9153
9.1875	262000	0.5148	0.5198	0.9155
9.2050	262500	0.4882	0.5116	0.9160
9.2226	263000	0.4964	0.5139	0.9155
9.2401	263500	0.4792	0.5284	0.9153
9.2576	264000	0.5089	0.5175	0.9154
9.2752	264500	0.5124	0.5188	0.9154
9.2927	265000	0.4968	0.5153	0.9152
9.3102	265500	0.5454	0.5129	0.9152
9.3278	266000	0.4858	0.5209	0.9147
9.3453	266500	0.4822	0.5257	0.9148
9.3628	267000	0.5343	0.5298	0.9148
9.3804	267500	0.5443	0.5303	0.9145
9.3979	268000	0.546	0.5204	0.9153
9.4154	268500	0.5253	0.5326	0.9154
9.4330	269000	0.5062	0.5270	0.9154
9.4505	269500	0.4901	0.5284	0.9150
9.4680	270000	0.5675	0.5271	0.9154
9.4856	270500	0.4831	0.5263	0.9152
9.5031	271000	0.4873	0.5256	0.9152
9.5206	271500	0.4576	0.5208	0.9155
9.5382	272000	0.5392	0.5250	0.9154
9.5557	272500	0.4716	0.5238	0.9158
9.5732	273000	0.5202	0.5282	0.9156
9.5908	273500	0.5036	0.5284	0.9149
9.6083	274000	0.4645	0.5216	0.9151
9.6258	274500	0.4683	0.5273	0.9154
9.6434	275000	0.4881	0.5307	0.9154
9.6609	275500	0.4677	0.5234	0.9155
9.6784	276000	0.54	0.5212	0.9153
9.6960	276500	0.4948	0.5277	0.9150
9.7135	277000	0.5008	0.5293	0.9150
9.7310	277500	0.4907	0.5307	0.9147
9.7486	278000	0.4876	0.5276	0.9144
9.7661	278500	0.539	0.5324	0.9145
9.7836	279000	0.5147	0.5325	0.9145
9.8012	279500	0.5095	0.5367	0.9150
9.8187	280000	0.476	0.5333	0.9147
9.8362	280500	0.5189	0.5325	0.9150
9.8538	281000	0.4633	0.5342	0.9149
9.8713	281500	0.5199	0.5314	0.9146
9.8888	282000	0.4645	0.5312	0.9151
9.9064	282500	0.4702	0.5339	0.9151
9.9239	283000	0.4609	0.5362	0.9151
9.9414	283500	0.4365	0.5340	0.9152
9.9590	284000	0.4587	0.5339	0.9152
9.9765	284500	0.4861	0.5355	0.9153
9.9940	285000	0.4473	0.5352	0.9153

</details>

Framework Versions

—Python: 3.10.10
—Sentence Transformers: 3.4.0.dev0
—Transformers: 4.46.3
—PyTorch: 2.5.1+cu124
—Accelerate: 0.34.2
—Datasets: 2.21.0
—Tokenizers: 0.20.3

Citation

BibTeX

Sentence Transformers

bibtex

@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",
}

MultipleNegativesRankingLoss

bibtex

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

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