avsolatorio/all-MiniLM-L6-v2-MEDI-MTEB-triplet-randproj-trainable-512-best

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 <!-- at revision fa97f6e7cb1a59073dff9e6b13e2715cf7475ac9 -->
• —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, 'requires_grad': True})
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("avsolatorio/all-MiniLM-L6-v2-MEDI-MTEB-triplet-randproj-trainable-512-best")
# Run inference
sentences = [
    'Should I stay or should I go?',
    'The aim of this study was to examine the experiences of parents encountering the critical deterioration and resuscitative care of other children in the pediatric intensive care unit where their own child was admitted.Grounded theory qualitative methodology.Pediatric intensive care unit of a pediatric tertiary care center in Montreal, Canada.Ten parents of critically ill children who witnessed resuscitative measures on another child.None.Semistructured interviews were conducted. While witnessing resuscitation, parents struggled with "Should I stay or should I go?" Their decision depended on specific contributing factors that were intrinsic to parents (curiosity or apprehension, the child\'s sake, trust or distrust) or extrinsic (limited space). These parents were not "spectators." Despite using coping strategies, the experiences were distressing in the majority of cases, although sometimes comforting. The impact on witnessing critical events had divergent effects on parental trust with healthcare professionals.',
    'Several recent studies suggest that acceleration of the head at impact during sporting activities may have a detrimental effect on cognitive function. Reducing acceleration of impact in these sports could reduce neurologic sequelae.To measure the effectiveness of a regulation football helmet to reduce acceleration of impact for both low- and moderate-force impacts.An experimental paired study design was used. Male volunteers between 16 and 30 years of age headed soccer balls traveling approximately 35 miles per hour bareheaded and with a helmet. An intraoral accelerometer worn inside a plastic mouthpiece measured acceleration of the head. The helmet also had an accelerometer placed inside the padding. For more forceful impacts, cadaver heads, both with and without helmets, were instrumented with intraoral (IO) and intracranial (IC) accelerometers and struck with a pendulum device. Simultaneous IO and IC accelerations were measured and compared between helmeted and unhelmeted cadaver heads. The main outcome was mean peak acceleration of the head and/or brain associated with low- and moderate-force impacts with and without protective headgear.Mean peak Gs, measured by the mouthpiece accelerometer, were significantly reduced when the participants heading soccer balls were wearing a helmet (7.7 Gs with vs 19.2 Gs without, p = 0.01). Wearing a helmet also significantly lowered the peak Gs measured intraorally and intracranially in cadavers subjected to moderate-force pendulum impacts: 28.7 Gs with vs 62.6 Gs without, p<0.001; and 56.4 Gs with vs 81.6 Gs without, p<0.001, respectively.',
]
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>

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Training Details

Training Datasets

NQ

• —Dataset: NQ
• —Size: 49,676 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: 11.84 tokens</li><li>max: 25 tokens</li></ul> | <ul><li>min: 110 tokens</li><li>mean: 138.08 tokens</li><li>max: 211 tokens</li></ul> | <ul><li>min: 111 tokens</li><li>mean: 138.38 tokens</li><li>max: 252 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

pubmed

• —Dataset: pubmed
• —Size: 29,908 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: 22.86 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 74 tokens</li><li>mean: 239.63 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 64 tokens</li><li>mean: 240.96 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

spectertraintriples

• —Dataset: spectertraintriples
• —Size: 49,676 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: 15.31 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 13.8 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 15.7 tokens</li><li>max: 68 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

S2ORCcitationsabstracts

• —Dataset: S2ORCcitationsabstracts
• —Size: 99,352 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: 27 tokens</li><li>mean: 202.95 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 205.71 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 204.68 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

fever

• —Dataset: fever
• —Size: 74,514 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: 12.36 tokens</li><li>max: 51 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 112.22 tokens</li><li>max: 148 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 113.94 tokens</li><li>max: 158 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

gooaq_pairs

• —Dataset: gooaq_pairs
• —Size: 24,838 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: 11.84 tokens</li><li>max: 24 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 60.08 tokens</li><li>max: 144 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 63.21 tokens</li><li>max: 165 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

codesearchnet

• —Dataset: codesearchnet
• —Size: 15,210 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: 29.23 tokens</li><li>max: 163 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 133.98 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 161.35 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

wikihow

• —Dataset: wikihow
• —Size: 5,070 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: 8.03 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 44.27 tokens</li><li>max: 89 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 36.71 tokens</li><li>max: 100 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

WikiAnswers

• —Dataset: WikiAnswers
• —Size: 24,838 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: 12.85 tokens</li><li>max: 39 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 12.95 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 13.06 tokens</li><li>max: 43 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

eli5questionanswer

• —Dataset: eli5questionanswer
• —Size: 24,838 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: 20.78 tokens</li><li>max: 63 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 98.02 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 109.02 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

amazon-qa

• —Dataset: amazon-qa
• —Size: 99,352 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: 22.78 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 53.82 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 62.55 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

medmcqa

• —Dataset: medmcqa
• —Size: 29,908 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: 20.65 tokens</li><li>max: 180 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 113.32 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 117.89 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

zeroshot

• —Dataset: zeroshot
• —Size: 15,210 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: 8.57 tokens</li><li>max: 20 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 110.88 tokens</li><li>max: 174 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 116.58 tokens</li><li>max: 192 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

TriviaQA_pairs

• —Dataset: TriviaQA_pairs
• —Size: 49,676 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: 19.27 tokens</li><li>max: 64 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 244.2 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 56 tokens</li><li>mean: 235.19 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

PAQ_pairs

• —Dataset: PAQ_pairs
• —Size: 24,838 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: 12.61 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 112 tokens</li><li>mean: 136.23 tokens</li><li>max: 225 tokens</li></ul> | <ul><li>min: 108 tokens</li><li>mean: 135.98 tokens</li><li>max: 254 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

stackexchangeduplicatequestionstitle-bodytitle-body

• —Dataset: stackexchangeduplicatequestionstitle-bodytitle-body
• —Size: 24,838 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: 16 tokens</li><li>mean: 150.03 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 138.73 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 199.2 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

trex

• —Dataset: trex
• —Size: 29,908 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: 9.57 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 21 tokens</li><li>mean: 103.3 tokens</li><li>max: 193 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 117.84 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

flickr30k_captions

• —Dataset: flickr30k_captions
• —Size: 24,838 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: 15.71 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 16.19 tokens</li><li>max: 64 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 16.43 tokens</li><li>max: 52 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

hotpotqa

• —Dataset: hotpotqa
• —Size: 40,048 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: 24.82 tokens</li><li>max: 110 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 112.64 tokens</li><li>max: 146 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 114.86 tokens</li><li>max: 178 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task671ambigqatext_generation

• —Dataset: task671ambigqatext_generation
• —Size: 1,018 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: 11 tokens</li><li>mean: 12.7 tokens</li><li>max: 26 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 12.52 tokens</li><li>max: 23 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 12.23 tokens</li><li>max: 19 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task061ropesanswer_generation

• —Dataset: task061ropesanswer_generation
• —Size: 1,018 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: 117 tokens</li><li>mean: 210.02 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 117 tokens</li><li>mean: 209.38 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 119 tokens</li><li>mean: 211.18 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task285imdbanswer_generation

• —Dataset: task285imdbanswer_generation
• —Size: 1,018 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: 46 tokens</li><li>mean: 209.41 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 49 tokens</li><li>mean: 203.91 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 209.41 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task905hatespeechoffensiveclassification

• —Dataset: task905hatespeechoffensiveclassification
• —Size: 1,018 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: 15 tokens</li><li>mean: 41.18 tokens</li><li>max: 164 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 40.19 tokens</li><li>max: 198 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 31.8 tokens</li><li>max: 135 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task566circaclassification

• —Dataset: task566circaclassification
• —Size: 1,018 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: 20 tokens</li><li>mean: 27.83 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 27.23 tokens</li><li>max: 44 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 27.51 tokens</li><li>max: 47 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task184snlientailmenttoneutraltextmodification

• —Dataset: task184snlientailmenttoneutraltextmodification
• —Size: 1,018 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: 17 tokens</li><li>mean: 29.81 tokens</li><li>max: 72 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 28.92 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 30.3 tokens</li><li>max: 100 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task280stereosetclassificationstereotypetype

• —Dataset: task280stereosetclassificationstereotypetype
• —Size: 1,018 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: 18.5 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 16.84 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 16.87 tokens</li><li>max: 51 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1599smcalflowclassification

• —Dataset: task1599smcalflowclassification
• —Size: 1,018 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: 11.34 tokens</li><li>max: 37 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 10.56 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 16.3 tokens</li><li>max: 45 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1384dealornodialog_classification

• —Dataset: task1384dealornodialog_classification
• —Size: 1,018 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: 14 tokens</li><li>mean: 59.36 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 59.64 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 58.78 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task591sciqanswer_generation

• —Dataset: task591sciqanswer_generation
• —Size: 1,018 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: 17.57 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.14 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 16.71 tokens</li><li>max: 75 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task823peixian-rtgendersentiment_analysis

• —Dataset: task823peixian-rtgendersentiment_analysis
• —Size: 1,018 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: 16 tokens</li><li>mean: 57.13 tokens</li><li>max: 179 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 59.67 tokens</li><li>max: 153 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 60.2 tokens</li><li>max: 169 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task023cosmosqaquestion_generation

• —Dataset: task023cosmosqaquestion_generation
• —Size: 1,018 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: 35 tokens</li><li>mean: 78.87 tokens</li><li>max: 159 tokens</li></ul> | <ul><li>min: 34 tokens</li><li>mean: 80.11 tokens</li><li>max: 165 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 79.1 tokens</li><li>max: 161 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task900freebaseqacategoryclassification

• —Dataset: task900freebaseqacategoryclassification
• —Size: 1,018 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: 20.4 tokens</li><li>max: 88 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 18.23 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 19.02 tokens</li><li>max: 69 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task924event2mindword_generation

• —Dataset: task924event2mindword_generation
• —Size: 1,018 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: 17 tokens</li><li>mean: 32.06 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: 31.44 tokens</li><li>max: 68 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task152tomqafindlocationeasy_noise

• —Dataset: task152tomqafindlocationeasy_noise
• —Size: 1,018 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: 37 tokens</li><li>mean: 53.08 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 52.45 tokens</li><li>max: 78 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 52.77 tokens</li><li>max: 82 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1368healthfactsentence_generation

• —Dataset: task1368healthfactsentence_generation
• —Size: 1,018 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: 91 tokens</li><li>mean: 240.4 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 84 tokens</li><li>mean: 239.58 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 97 tokens</li><li>mean: 245.19 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1661superglue_classification

• —Dataset: task1661superglue_classification
• —Size: 1,018 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: 35 tokens</li><li>mean: 141.18 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 143.01 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 143.2 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1187politifactclassification

• —Dataset: task1187politifactclassification
• —Size: 1,018 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: 14 tokens</li><li>mean: 33.28 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 31.53 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 31.93 tokens</li><li>max: 71 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1728webnlgdatato_text

• —Dataset: task1728webnlgdatato_text
• —Size: 1,018 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: 42.96 tokens</li><li>max: 152 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 46.5 tokens</li><li>max: 152 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 42.77 tokens</li><li>max: 152 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task112assetsimplesentenceidentification

• —Dataset: task112assetsimplesentenceidentification
• —Size: 1,018 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: 18 tokens</li><li>mean: 51.97 tokens</li><li>max: 136 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 51.73 tokens</li><li>max: 144 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 51.88 tokens</li><li>max: 114 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1340msrtextcompressioncompression

• —Dataset: task1340msrtextcompressioncompression
• —Size: 1,018 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: 14 tokens</li><li>mean: 41.88 tokens</li><li>max: 116 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 44.35 tokens</li><li>max: 133 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.06 tokens</li><li>max: 141 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task072abductivenlianswer_generation

• —Dataset: task072abductivenlianswer_generation
• —Size: 1,018 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: 17 tokens</li><li>mean: 26.88 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 26.17 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 26.41 tokens</li><li>max: 55 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1504hatexplainanswer_generation

• —Dataset: task1504hatexplainanswer_generation
• —Size: 1,018 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: 28.86 tokens</li><li>max: 72 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 24.52 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 28.07 tokens</li><li>max: 67 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task684onlineprivacypolicytextinformationtype_generation

• —Dataset: task684onlineprivacypolicytextinformationtype_generation
• —Size: 1,018 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: 29.9 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 30.16 tokens</li><li>max: 61 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 30.06 tokens</li><li>max: 68 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1290xsumsummarization

• —Dataset: task1290xsumsummarization
• —Size: 1,018 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: 39 tokens</li><li>mean: 226.47 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 50 tokens</li><li>mean: 229.89 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 34 tokens</li><li>mean: 229.29 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task075squad1.1answer_generation

• —Dataset: task075squad1.1answer_generation
• —Size: 1,018 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: 48 tokens</li><li>mean: 168.28 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 45 tokens</li><li>mean: 172.9 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 179.79 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1587scifactclassification

• —Dataset: task1587scifactclassification
• —Size: 1,018 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: 88 tokens</li><li>mean: 242.74 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 90 tokens</li><li>mean: 246.86 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 86 tokens</li><li>mean: 244.66 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task384socialiqaquestion_classification

• —Dataset: task384socialiqaquestion_classification
• —Size: 1,018 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: 24 tokens</li><li>mean: 35.43 tokens</li><li>max: 78 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 34.4 tokens</li><li>max: 59 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 34.6 tokens</li><li>max: 57 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1555scitailanswer_generation

• —Dataset: task1555scitailanswer_generation
• —Size: 1,018 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: 18 tokens</li><li>mean: 36.84 tokens</li><li>max: 90 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 36.35 tokens</li><li>max: 80 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 36.61 tokens</li><li>max: 92 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1532dailydialogemotionclassification

• —Dataset: task1532dailydialogemotionclassification
• —Size: 1,018 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: 16 tokens</li><li>mean: 136.34 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 141.12 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 135.54 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task239tweetqaanswer_generation

• —Dataset: task239tweetqaanswer_generation
• —Size: 1,018 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: 28 tokens</li><li>mean: 56.04 tokens</li><li>max: 91 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 56.6 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 56.03 tokens</li><li>max: 81 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task596mochaquestion_generation

• —Dataset: task596mochaquestion_generation
• —Size: 1,018 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: 80.75 tokens</li><li>max: 163 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 96.28 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 44.76 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1411dartsubject_identification

• —Dataset: task1411dartsubject_identification
• —Size: 1,018 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: 14.91 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 14.08 tokens</li><li>max: 37 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 14.34 tokens</li><li>max: 38 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1359numersenseanswergeneration

• —Dataset: task1359numersenseanswergeneration
• —Size: 1,018 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: 18.77 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 18.41 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 18.35 tokens</li><li>max: 30 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task329gapclassification

• —Dataset: task329gapclassification
• —Size: 1,018 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: 40 tokens</li><li>mean: 123.98 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 62 tokens</li><li>mean: 127.13 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 58 tokens</li><li>mean: 128.92 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task220rocstoriestitle_classification

• —Dataset: task220rocstoriestitle_classification
• —Size: 1,018 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: 53 tokens</li><li>mean: 80.86 tokens</li><li>max: 116 tokens</li></ul> | <ul><li>min: 51 tokens</li><li>mean: 81.24 tokens</li><li>max: 108 tokens</li></ul> | <ul><li>min: 55 tokens</li><li>mean: 79.88 tokens</li><li>max: 115 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task316crows-pairsclassification_stereotype

• —Dataset: task316crows-pairsclassification_stereotype
• —Size: 1,018 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: 19.8 tokens</li><li>max: 51 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 18.23 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.89 tokens</li><li>max: 52 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task495semevalheadline_classification

• —Dataset: task495semevalheadline_classification
• —Size: 1,018 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: 17 tokens</li><li>mean: 24.5 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 24.16 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 24.26 tokens</li><li>max: 38 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1168browncoarsepostagging

• —Dataset: task1168browncoarsepostagging
• —Size: 1,018 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: 13 tokens</li><li>mean: 43.79 tokens</li><li>max: 142 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 43.05 tokens</li><li>max: 197 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 44.64 tokens</li><li>max: 197 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task348squad2.0unanswerablequestiongeneration

• —Dataset: task348squad2.0unanswerablequestiongeneration
• —Size: 1,018 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: 30 tokens</li><li>mean: 153.11 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 161.73 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 167.0 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task049multircquestionsneededto_answer

• —Dataset: task049multircquestionsneededto_answer
• —Size: 1,018 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: 174 tokens</li><li>mean: 252.74 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 169 tokens</li><li>mean: 252.74 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 178 tokens</li><li>mean: 252.9 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1534dailydialogquestionclassification

• —Dataset: task1534dailydialogquestionclassification
• —Size: 1,018 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: 17 tokens</li><li>mean: 126.44 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 131.14 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 136.07 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task322jigsawclassification_threat

• —Dataset: task322jigsawclassification_threat
• —Size: 1,018 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: 55.03 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 61.38 tokens</li><li>max: 249 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 62.47 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task295semeval2020task4commonsense_reasoning

• —Dataset: task295semeval2020task4commonsense_reasoning
• —Size: 1,018 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: 25 tokens</li><li>mean: 44.9 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 45.21 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 44.7 tokens</li><li>max: 88 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task186snlicontradictiontoentailmenttextmodification

• —Dataset: task186snlicontradictiontoentailmenttextmodification
• —Size: 1,018 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: 18 tokens</li><li>mean: 31.18 tokens</li><li>max: 102 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 30.14 tokens</li><li>max: 65 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 32.19 tokens</li><li>max: 67 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task034winograndequestionmodificationobject

• —Dataset: task034winograndequestionmodificationobject
• —Size: 1,018 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: 29 tokens</li><li>mean: 36.37 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 35.59 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 34.87 tokens</li><li>max: 55 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task160replaceletterina_sentence

• —Dataset: task160replaceletterina_sentence
• —Size: 1,018 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: 29 tokens</li><li>mean: 31.98 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.75 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 31.75 tokens</li><li>max: 48 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task469mrqaanswer_generation

• —Dataset: task469mrqaanswer_generation
• —Size: 1,018 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: 27 tokens</li><li>mean: 182.31 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 181.14 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 184.24 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task105storycloze-rocstoriessentencegeneration

• —Dataset: task105storycloze-rocstoriessentencegeneration
• —Size: 1,018 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: 36 tokens</li><li>mean: 55.56 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 54.95 tokens</li><li>max: 76 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 55.97 tokens</li><li>max: 76 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task649raceblankquestiongeneration

• —Dataset: task649raceblankquestiongeneration
• —Size: 1,018 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: 36 tokens</li><li>mean: 252.97 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 252.53 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 157 tokens</li><li>mean: 254.0 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1536dailydialoghappinessclassification

• —Dataset: task1536dailydialoghappinessclassification
• —Size: 1,018 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: 13 tokens</li><li>mean: 127.43 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 133.98 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 142.13 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task683onlineprivacypolicytextpurposeanswer_generation

• —Dataset: task683onlineprivacypolicytextpurposeanswer_generation
• —Size: 1,018 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: 29.92 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 30.2 tokens</li><li>max: 64 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 29.84 tokens</li><li>max: 68 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task024cosmosqaanswer_generation

• —Dataset: task024cosmosqaanswer_generation
• —Size: 1,018 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: 45 tokens</li><li>mean: 92.82 tokens</li><li>max: 176 tokens</li></ul> | <ul><li>min: 47 tokens</li><li>mean: 93.13 tokens</li><li>max: 174 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 94.96 tokens</li><li>max: 183 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task584udepsengfinepos_tagging

• —Dataset: task584udepsengfinepos_tagging
• —Size: 1,018 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: 40.09 tokens</li><li>max: 120 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 39.33 tokens</li><li>max: 186 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.42 tokens</li><li>max: 148 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task066timetravelbinaryconsistencyclassification

• —Dataset: task066timetravelbinaryconsistencyclassification
• —Size: 1,018 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: 42 tokens</li><li>mean: 66.75 tokens</li><li>max: 93 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 67.37 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 45 tokens</li><li>mean: 67.13 tokens</li><li>max: 92 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task413mickeyensentenceperturbation_generation

• —Dataset: task413mickeyensentenceperturbation_generation
• —Size: 1,018 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: 13.72 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 13.8 tokens</li><li>max: 21 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 13.28 tokens</li><li>max: 20 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task182duorcquestion_generation

• —Dataset: task182duorcquestion_generation
• —Size: 1,018 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: 99 tokens</li><li>mean: 242.87 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 120 tokens</li><li>mean: 246.6 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 99 tokens</li><li>mean: 246.31 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task028dropanswer_generation

• —Dataset: task028dropanswer_generation
• —Size: 1,018 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: 76 tokens</li><li>mean: 230.68 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 86 tokens</li><li>mean: 234.65 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 81 tokens</li><li>mean: 236.16 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1601webquestionsanswer_generation

• —Dataset: task1601webquestionsanswer_generation
• —Size: 1,018 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: 16.54 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 16.68 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 16.75 tokens</li><li>max: 27 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1295adversarialqaquestionanswering

• —Dataset: task1295adversarialqaquestionanswering
• —Size: 1,018 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: 45 tokens</li><li>mean: 165.69 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 54 tokens</li><li>mean: 166.56 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 167.89 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task201mnlineutral_classification

• —Dataset: task201mnlineutral_classification
• —Size: 1,018 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: 24 tokens</li><li>mean: 72.88 tokens</li><li>max: 218 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 73.52 tokens</li><li>max: 170 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 72.82 tokens</li><li>max: 205 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task038qasccombined_fact

• —Dataset: task038qasccombined_fact
• —Size: 1,018 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: 18 tokens</li><li>mean: 31.28 tokens</li><li>max: 57 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 30.54 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 30.82 tokens</li><li>max: 53 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task293storycommonsenseemotiontextgeneration

• —Dataset: task293storycommonsenseemotiontextgeneration
• —Size: 1,018 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: 14 tokens</li><li>mean: 40.64 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 40.58 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 38.51 tokens</li><li>max: 86 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task572recipenlgtextgeneration

• —Dataset: task572recipenlgtextgeneration
• —Size: 1,018 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: 24 tokens</li><li>mean: 114.35 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 119.45 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 123.81 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task517emoclassifyemotionof_dialogue

• —Dataset: task517emoclassifyemotionof_dialogue
• —Size: 1,018 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: 18.16 tokens</li><li>max: 78 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 16.94 tokens</li><li>max: 59 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 18.35 tokens</li><li>max: 67 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task382hybridqaanswer_generation

• —Dataset: task382hybridqaanswer_generation
• —Size: 1,018 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: 29 tokens</li><li>mean: 42.25 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 29 tokens</li><li>mean: 41.63 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 41.83 tokens</li><li>max: 75 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task176breakdecompose_questions

• —Dataset: task176breakdecompose_questions
• —Size: 1,018 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: 17.41 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.22 tokens</li><li>max: 39 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 15.72 tokens</li><li>max: 38 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1291multinews_summarization

• —Dataset: task1291multinews_summarization
• —Size: 1,018 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: 116 tokens</li><li>mean: 255.36 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 146 tokens</li><li>mean: 255.71 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 68 tokens</li><li>mean: 252.09 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task155countnouns_verbs

• —Dataset: task155countnouns_verbs
• —Size: 1,018 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: 23 tokens</li><li>mean: 27.01 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 26.79 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 26.96 tokens</li><li>max: 46 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task031winograndequestiongenerationobject

• —Dataset: task031winograndequestiongenerationobject
• —Size: 1,018 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: 7.41 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: 7.27 tokens</li><li>max: 11 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task279stereosetclassification_stereotype

• —Dataset: task279stereosetclassification_stereotype
• —Size: 1,018 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: 17.86 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 15.56 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.31 tokens</li><li>max: 50 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1336peixianequityevaluationcorpusgenderclassifier

• —Dataset: task1336peixianequityevaluationcorpusgenderclassifier
• —Size: 1,018 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: 9.61 tokens</li><li>max: 17 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.59 tokens</li><li>max: 16 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 9.66 tokens</li><li>max: 16 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task508scruplesdilemmasmoreethical_isidentifiable

• —Dataset: task508scruplesdilemmasmoreethical_isidentifiable
• —Size: 1,018 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: 29.76 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 28.61 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 28.63 tokens</li><li>max: 86 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task518emodifferentdialogueemotions

• —Dataset: task518emodifferentdialogueemotions
• —Size: 1,018 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: 28 tokens</li><li>mean: 47.87 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 45.55 tokens</li><li>max: 116 tokens</li></ul> | <ul><li>min: 26 tokens</li><li>mean: 45.87 tokens</li><li>max: 123 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task077splashexplanationtosql

• —Dataset: task077splashexplanationtosql
• —Size: 1,018 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: 39.82 tokens</li><li>max: 126 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 40.04 tokens</li><li>max: 126 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 35.69 tokens</li><li>max: 111 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task923event2mindclassifier

• —Dataset: task923event2mindclassifier
• —Size: 1,018 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: 20.66 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 18.63 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 19.53 tokens</li><li>max: 46 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task470mrqaquestion_generation

• —Dataset: task470mrqaquestion_generation
• —Size: 1,018 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: 13 tokens</li><li>mean: 170.62 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 173.14 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 178.86 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task638multiwoz_classification

• —Dataset: task638multiwoz_classification
• —Size: 1,018 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: 78 tokens</li><li>mean: 223.5 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 76 tokens</li><li>mean: 220.19 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 64 tokens</li><li>mean: 220.04 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1412webquestionsquestionanswering

• —Dataset: task1412webquestionsquestionanswering
• —Size: 1,018 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: 10.32 tokens</li><li>max: 17 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.18 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:

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

task847pubmedqaquestion_generation

• —Dataset: task847pubmedqaquestion_generation
• —Size: 1,018 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: 249.63 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 21 tokens</li><li>mean: 249.29 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 249.18 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task678ollieactualrelationshipanswer_generation

• —Dataset: task678ollieactualrelationshipanswer_generation
• —Size: 1,018 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: 20 tokens</li><li>mean: 41.02 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 38.03 tokens</li><li>max: 102 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 41.19 tokens</li><li>max: 104 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task290tellmewhyquestion_answerability

• —Dataset: task290tellmewhyquestion_answerability
• —Size: 1,018 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: 37 tokens</li><li>mean: 62.8 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 62.28 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 62.92 tokens</li><li>max: 95 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task575airdialogue_classification

• —Dataset: task575airdialogue_classification
• —Size: 1,018 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: 14.16 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 13.56 tokens</li><li>max: 43 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 12.33 tokens</li><li>max: 42 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task189snlineutraltocontradictiontextmodification

• —Dataset: task189snlineutraltocontradictiontextmodification
• —Size: 1,018 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: 18 tokens</li><li>mean: 31.85 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 30.74 tokens</li><li>max: 57 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 33.3 tokens</li><li>max: 105 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task026dropquestion_generation

• —Dataset: task026dropquestion_generation
• —Size: 1,018 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: 82 tokens</li><li>mean: 219.29 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 57 tokens</li><li>mean: 222.74 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 96 tokens</li><li>mean: 231.78 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task162countwordsstartingwith_letter

• —Dataset: task162countwordsstartingwith_letter
• —Size: 1,018 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: 28 tokens</li><li>mean: 32.21 tokens</li><li>max: 56 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.76 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 31.63 tokens</li><li>max: 46 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task079conalaconcat_strings

• —Dataset: task079conalaconcat_strings
• —Size: 1,018 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: 11 tokens</li><li>mean: 39.59 tokens</li><li>max: 76 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 34.2 tokens</li><li>max: 80 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 33.73 tokens</li><li>max: 76 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task610conllppner

• —Dataset: task610conllppner
• —Size: 1,018 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: 19.53 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 20.2 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 14.13 tokens</li><li>max: 54 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task046miscellaneousquestion_typing

• —Dataset: task046miscellaneousquestion_typing
• —Size: 1,018 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: 16 tokens</li><li>mean: 25.34 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 24.82 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 25.11 tokens</li><li>max: 57 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task197mnlidomainanswergeneration

• —Dataset: task197mnlidomainanswergeneration
• —Size: 1,018 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: 15 tokens</li><li>mean: 43.82 tokens</li><li>max: 197 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 44.72 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:

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

task1325qazrequestiongenerationonsubject_relation

• —Dataset: task1325qazrequestiongenerationonsubject_relation
• —Size: 1,018 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: 18 tokens</li><li>mean: 50.73 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 49.55 tokens</li><li>max: 180 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 54.03 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task430sentevalsubject_count

• —Dataset: task430sentevalsubject_count
• —Size: 1,018 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: 17.3 tokens</li><li>max: 35 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.39 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 16.22 tokens</li><li>max: 34 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task672_nummersense

• —Dataset: task672_nummersense
• —Size: 1,018 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: 15.72 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.3 tokens</li><li>max: 27 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.26 tokens</li><li>max: 30 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task402grailqaparaphrase_generation

• —Dataset: task402grailqaparaphrase_generation
• —Size: 1,018 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: 23 tokens</li><li>mean: 130.07 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 24 tokens</li><li>mean: 139.63 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 136.8 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task904hatespeechoffensiveclassification

• —Dataset: task904hatespeechoffensiveclassification
• —Size: 1,018 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: 34.21 tokens</li><li>max: 157 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 33.94 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 27.51 tokens</li><li>max: 148 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task192hotpotqasentence_generation

• —Dataset: task192hotpotqasentence_generation
• —Size: 1,018 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: 37 tokens</li><li>mean: 125.68 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 35 tokens</li><li>mean: 124.36 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 133.49 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task069abductivenliclassification

• —Dataset: task069abductivenliclassification
• —Size: 1,018 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: 33 tokens</li><li>mean: 52.06 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 52.09 tokens</li><li>max: 95 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 51.87 tokens</li><li>max: 95 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task574airdialoguesentencegeneration

• —Dataset: task574airdialoguesentencegeneration
• —Size: 1,018 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: 54 tokens</li><li>mean: 144.3 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 57 tokens</li><li>mean: 143.64 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 66 tokens</li><li>mean: 147.62 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task187snlientailmenttocontradictiontextmodification

• —Dataset: task187snlientailmenttocontradictiontextmodification
• —Size: 1,018 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: 16 tokens</li><li>mean: 30.16 tokens</li><li>max: 69 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 30.0 tokens</li><li>max: 104 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 29.36 tokens</li><li>max: 71 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task749glucosereversecauseemotion_detection

• —Dataset: task749glucosereversecauseemotion_detection
• —Size: 1,018 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: 38 tokens</li><li>mean: 67.56 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 67.11 tokens</li><li>max: 104 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 68.44 tokens</li><li>max: 107 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1552scitailquestion_generation

• —Dataset: task1552scitailquestion_generation
• —Size: 1,018 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: 18.34 tokens</li><li>max: 53 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.55 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 15.92 tokens</li><li>max: 54 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task750aquamultiplechoiceanswering

• —Dataset: task750aquamultiplechoiceanswering
• —Size: 1,018 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: 33 tokens</li><li>mean: 70.42 tokens</li><li>max: 194 tokens</li></ul> | <ul><li>min: 32 tokens</li><li>mean: 68.55 tokens</li><li>max: 194 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 68.5 tokens</li><li>max: 165 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task327jigsawclassification_toxic

• —Dataset: task327jigsawclassification_toxic
• —Size: 1,018 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: 37.15 tokens</li><li>max: 234 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 41.69 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 46.13 tokens</li><li>max: 244 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1502hatexplainclassification

• —Dataset: task1502hatexplainclassification
• —Size: 1,018 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: 28.69 tokens</li><li>max: 73 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 26.72 tokens</li><li>max: 110 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 26.94 tokens</li><li>max: 90 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task328jigsawclassification_insult

• —Dataset: task328jigsawclassification_insult
• —Size: 1,018 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: 51.2 tokens</li><li>max: 247 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 60.74 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 64.45 tokens</li><li>max: 249 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task304numericfusedheadresolution

• —Dataset: task304numericfusedheadresolution
• —Size: 1,018 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: 15 tokens</li><li>mean: 120.8 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 121.88 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 134.4 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1293kilttaskshotpotqaquestion_answering

• —Dataset: task1293kilttaskshotpotqaquestion_answering
• —Size: 1,018 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: 24.64 tokens</li><li>max: 114 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 24.23 tokens</li><li>max: 114 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 23.72 tokens</li><li>max: 84 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task216rocstoriescorrectanswergeneration

• —Dataset: task216rocstoriescorrectanswergeneration
• —Size: 1,018 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: 39 tokens</li><li>mean: 59.39 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 58.25 tokens</li><li>max: 92 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 58.03 tokens</li><li>max: 95 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1326qazrequestiongenerationfromanswer

• —Dataset: task1326qazrequestiongenerationfromanswer
• —Size: 1,018 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: 17 tokens</li><li>mean: 46.52 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 45.41 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 49.19 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1338peixianequityevaluationcorpussentimentclassifier

• —Dataset: task1338peixianequityevaluationcorpussentimentclassifier
• —Size: 1,018 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: 9.71 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> | <ul><li>min: 6 tokens</li><li>mean: 9.6 tokens</li><li>max: 17 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1729personachatgenerate_next

• —Dataset: task1729personachatgenerate_next
• —Size: 1,018 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: 44 tokens</li><li>mean: 146.41 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 43 tokens</li><li>mean: 142.25 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 50 tokens</li><li>mean: 144.54 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1202atomicclassification_xneed

• —Dataset: task1202atomicclassification_xneed
• —Size: 1,018 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: 14 tokens</li><li>mean: 19.55 tokens</li><li>max: 32 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.38 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.24 tokens</li><li>max: 28 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task400pawsparaphrase_classification

• —Dataset: task400pawsparaphrase_classification
• —Size: 1,018 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: 19 tokens</li><li>mean: 52.27 tokens</li><li>max: 97 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 51.78 tokens</li><li>max: 98 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 53.05 tokens</li><li>max: 97 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task502scruplesanecdoteswhoiswrongverification

• —Dataset: task502scruplesanecdoteswhoiswrongverification
• —Size: 1,018 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: 230.21 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 236.63 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 235.13 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task088identifytypo_verification

• —Dataset: task088identifytypo_verification
• —Size: 1,018 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: 11 tokens</li><li>mean: 15.1 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 15.07 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 15.41 tokens</li><li>max: 47 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task221rocstoriestwochoiceclassification

• —Dataset: task221rocstoriestwochoiceclassification
• —Size: 1,018 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: 47 tokens</li><li>mean: 72.6 tokens</li><li>max: 108 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 72.61 tokens</li><li>max: 109 tokens</li></ul> | <ul><li>min: 46 tokens</li><li>mean: 73.22 tokens</li><li>max: 108 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task200mnlientailment_classification

• —Dataset: task200mnlientailment_classification
• —Size: 1,018 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: 24 tokens</li><li>mean: 72.98 tokens</li><li>max: 198 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 72.91 tokens</li><li>max: 224 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 74.11 tokens</li><li>max: 226 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task074squad1.1question_generation

• —Dataset: task074squad1.1question_generation
• —Size: 1,018 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: 30 tokens</li><li>mean: 149.8 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 160.42 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 164.58 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task581socialiqaquestion_generation

• —Dataset: task581socialiqaquestion_generation
• —Size: 1,018 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: 26.36 tokens</li><li>max: 69 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 25.61 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 25.76 tokens</li><li>max: 48 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1186nnehrngo_classification

• —Dataset: task1186nnehrngo_classification
• —Size: 1,018 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: 19 tokens</li><li>mean: 33.81 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 33.53 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 33.4 tokens</li><li>max: 77 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task898freebaseqaanswergeneration

• —Dataset: task898freebaseqaanswergeneration
• —Size: 1,018 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: 19.14 tokens</li><li>max: 125 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.5 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 17.33 tokens</li><li>max: 79 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1408dartsimilarity_classification

• —Dataset: task1408dartsimilarity_classification
• —Size: 1,018 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: 59.5 tokens</li><li>max: 147 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 61.98 tokens</li><li>max: 154 tokens</li></ul> | <ul><li>min: 20 tokens</li><li>mean: 48.3 tokens</li><li>max: 124 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task168strategyqaquestion_decomposition

• —Dataset: task168strategyqaquestion_decomposition
• —Size: 1,018 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: 42 tokens</li><li>mean: 80.45 tokens</li><li>max: 181 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 78.96 tokens</li><li>max: 179 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 77.07 tokens</li><li>max: 166 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1357xlsumsummary_generation

• —Dataset: task1357xlsumsummary_generation
• —Size: 1,018 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: 67 tokens</li><li>mean: 241.84 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 69 tokens</li><li>mean: 243.75 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 67 tokens</li><li>mean: 246.71 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task390torquetextspanselection

• —Dataset: task390torquetextspanselection
• —Size: 1,018 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: 47 tokens</li><li>mean: 110.13 tokens</li><li>max: 196 tokens</li></ul> | <ul><li>min: 42 tokens</li><li>mean: 110.78 tokens</li><li>max: 195 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 110.6 tokens</li><li>max: 196 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task165mcscriptquestionansweringcommonsense

• —Dataset: task165mcscriptquestionansweringcommonsense
• —Size: 1,018 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: 147 tokens</li><li>mean: 198.18 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 145 tokens</li><li>mean: 196.56 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 147 tokens</li><li>mean: 198.4 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1533dailydialogformalclassification

• —Dataset: task1533dailydialogformalclassification
• —Size: 1,018 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: 13 tokens</li><li>mean: 130.59 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 137.09 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 137.38 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task002quorefanswer_generation

• —Dataset: task002quorefanswer_generation
• —Size: 1,018 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: 214 tokens</li><li>mean: 255.57 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 214 tokens</li><li>mean: 255.53 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 224 tokens</li><li>mean: 255.61 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1297qascquestion_answering

• —Dataset: task1297qascquestion_answering
• —Size: 1,018 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: 61 tokens</li><li>mean: 84.55 tokens</li><li>max: 134 tokens</li></ul> | <ul><li>min: 59 tokens</li><li>mean: 85.56 tokens</li><li>max: 130 tokens</li></ul> | <ul><li>min: 58 tokens</li><li>mean: 84.73 tokens</li><li>max: 125 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task305jeopardyanswergenerationnormal

• —Dataset: task305jeopardyanswergenerationnormal
• —Size: 1,018 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: 27.6 tokens</li><li>max: 59 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 27.42 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 27.39 tokens</li><li>max: 46 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task029winograndefull_object

• —Dataset: task029winograndefull_object
• —Size: 1,018 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: 7.37 tokens</li><li>max: 12 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 7.33 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:

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

task1327qazreanswergenerationfromquestion

• —Dataset: task1327qazreanswergenerationfromquestion
• —Size: 1,018 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: 24 tokens</li><li>mean: 54.55 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 51.77 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 55.1 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task326jigsawclassification_obscene

• —Dataset: task326jigsawclassification_obscene
• —Size: 1,018 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: 65.28 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 77.4 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 73.69 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1542everyithelementfrom_starting

• —Dataset: task1542everyithelementfrom_starting
• —Size: 1,018 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: 13 tokens</li><li>mean: 124.81 tokens</li><li>max: 245 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 123.13 tokens</li><li>max: 244 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 120.4 tokens</li><li>max: 238 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task570recipenlgnergeneration

• —Dataset: task570recipenlgnergeneration
• —Size: 1,018 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: 73.85 tokens</li><li>max: 250 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 73.41 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 75.34 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1409darttext_generation

• —Dataset: task1409darttext_generation
• —Size: 1,018 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: 18 tokens</li><li>mean: 67.42 tokens</li><li>max: 174 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 72.58 tokens</li><li>max: 170 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 67.42 tokens</li><li>max: 164 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task401numericfusedheadreference

• —Dataset: task401numericfusedheadreference
• —Size: 1,018 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: 16 tokens</li><li>mean: 110.13 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 116.49 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 120.79 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task846pubmedqaclassification

• —Dataset: task846pubmedqaclassification
• —Size: 1,018 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: 32 tokens</li><li>mean: 85.71 tokens</li><li>max: 246 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 85.04 tokens</li><li>max: 225 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 93.66 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1712pokiclassification

• —Dataset: task1712pokiclassification
• —Size: 1,018 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: 52.65 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 55.69 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 63.02 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task344hybridqaanswer_generation

• —Dataset: task344hybridqaanswer_generation
• —Size: 1,018 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: 22.2 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 22.05 tokens</li><li>max: 58 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 22.14 tokens</li><li>max: 55 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task875emotionclassification

• —Dataset: task875emotionclassification
• —Size: 1,018 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: 23.06 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 18.42 tokens</li><li>max: 63 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 20.46 tokens</li><li>max: 68 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1214atomicclassification_xwant

• —Dataset: task1214atomicclassification_xwant
• —Size: 1,018 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: 14 tokens</li><li>mean: 19.67 tokens</li><li>max: 32 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.41 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:

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

task106scruplesethical_judgment

• —Dataset: task106scruplesethical_judgment
• —Size: 1,018 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: 29.99 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 28.92 tokens</li><li>max: 86 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 28.76 tokens</li><li>max: 58 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task238iircanswerfrompassageanswergeneration

• —Dataset: task238iircanswerfrompassageanswergeneration
• —Size: 1,018 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: 138 tokens</li><li>mean: 242.65 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 165 tokens</li><li>mean: 243.0 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 173 tokens</li><li>mean: 243.1 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1391winograndeeasyanswergeneration

• —Dataset: task1391winograndeeasyanswergeneration
• —Size: 1,018 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: 26 tokens</li><li>mean: 31.66 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>min: 26 tokens</li><li>mean: 31.34 tokens</li><li>max: 48 tokens</li></ul> | <ul><li>min: 25 tokens</li><li>mean: 31.16 tokens</li><li>max: 49 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task195sentiment140classification

• —Dataset: task195sentiment140classification
• —Size: 1,018 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: 22.7 tokens</li><li>max: 118 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 18.87 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 21.32 tokens</li><li>max: 51 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task163countwordsendingwith_letter

• —Dataset: task163countwordsendingwith_letter
• —Size: 1,018 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: 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: 31.59 tokens</li><li>max: 43 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task579socialiqaclassification

• —Dataset: task579socialiqaclassification
• —Size: 1,018 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: 39 tokens</li><li>mean: 54.07 tokens</li><li>max: 132 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 53.57 tokens</li><li>max: 103 tokens</li></ul> | <ul><li>min: 40 tokens</li><li>mean: 54.15 tokens</li><li>max: 84 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task569recipenlgtextgeneration

• —Dataset: task569recipenlgtextgeneration
• —Size: 1,018 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: 25 tokens</li><li>mean: 193.55 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 55 tokens</li><li>mean: 193.45 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 197.57 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1602webquestionquestion_genreation

• —Dataset: task1602webquestionquestion_genreation
• —Size: 1,018 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: 23.56 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 24.19 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 22.42 tokens</li><li>max: 120 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task747glucosecauseemotiondetection

• —Dataset: task747glucosecauseemotiondetection
• —Size: 1,018 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: 35 tokens</li><li>mean: 67.92 tokens</li><li>max: 112 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 68.12 tokens</li><li>max: 108 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 68.76 tokens</li><li>max: 99 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task219rocstoriestitleanswergeneration

• —Dataset: task219rocstoriestitleanswergeneration
• —Size: 1,018 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: 42 tokens</li><li>mean: 67.68 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: 66.86 tokens</li><li>max: 96 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task178quartzquestion_answering

• —Dataset: task178quartzquestion_answering
• —Size: 1,018 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: 28 tokens</li><li>mean: 57.92 tokens</li><li>max: 110 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 57.34 tokens</li><li>max: 111 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 56.88 tokens</li><li>max: 102 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task103facts2storylongtextgeneration

• —Dataset: task103facts2storylongtextgeneration
• —Size: 1,018 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: 52 tokens</li><li>mean: 80.36 tokens</li><li>max: 143 tokens</li></ul> | <ul><li>min: 51 tokens</li><li>mean: 82.32 tokens</li><li>max: 157 tokens</li></ul> | <ul><li>min: 49 tokens</li><li>mean: 79.01 tokens</li><li>max: 145 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task301recordquestion_generation

• —Dataset: task301recordquestion_generation
• —Size: 1,018 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: 140 tokens</li><li>mean: 210.77 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 139 tokens</li><li>mean: 209.96 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 143 tokens</li><li>mean: 208.7 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1369healthfactsentence_generation

• —Dataset: task1369healthfactsentence_generation
• —Size: 1,018 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: 110 tokens</li><li>mean: 242.84 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 101 tokens</li><li>mean: 242.29 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 113 tokens</li><li>mean: 251.55 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task515sentevaloddwordout

• —Dataset: task515sentevaloddwordout
• —Size: 1,018 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: 19.77 tokens</li><li>max: 36 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.13 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.04 tokens</li><li>max: 35 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task496semevalanswer_generation

• —Dataset: task496semevalanswer_generation
• —Size: 1,018 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: 28.15 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 27.81 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 27.71 tokens</li><li>max: 45 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1658billsumsummarization

• —Dataset: task1658billsumsummarization
• —Size: 1,018 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: 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:

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

task1204atomicclassification_hinderedby

• —Dataset: task1204atomicclassification_hinderedby
• —Size: 1,018 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: 14 tokens</li><li>mean: 21.99 tokens</li><li>max: 35 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 21.95 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 21.53 tokens</li><li>max: 38 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1392supergluemultircanswerverification

• —Dataset: task1392supergluemultircanswerverification
• —Size: 1,018 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: 128 tokens</li><li>mean: 242.19 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 127 tokens</li><li>mean: 242.46 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 136 tokens</li><li>mean: 242.46 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task306jeopardyanswergenerationdouble

• —Dataset: task306jeopardyanswergenerationdouble
• —Size: 1,018 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: 27.76 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 27.16 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:

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

task1286openbookqaquestion_answering

• —Dataset: task1286openbookqaquestion_answering
• —Size: 1,018 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: 39.48 tokens</li><li>max: 85 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 38.88 tokens</li><li>max: 96 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 38.37 tokens</li><li>max: 89 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task159checkfrequencyofwordsinsentence_pair

• —Dataset: task159checkfrequencyofwordsinsentence_pair
• —Size: 1,018 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: 44 tokens</li><li>mean: 50.33 tokens</li><li>max: 67 tokens</li></ul> | <ul><li>min: 44 tokens</li><li>mean: 50.32 tokens</li><li>max: 67 tokens</li></ul> | <ul><li>min: 44 tokens</li><li>mean: 50.55 tokens</li><li>max: 66 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task151tomqafindlocationeasy_clean

• —Dataset: task151tomqafindlocationeasy_clean
• —Size: 1,018 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: 37 tokens</li><li>mean: 50.73 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: 50.49 tokens</li><li>max: 74 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task323jigsawclassificationsexuallyexplicit

• —Dataset: task323jigsawclassificationsexuallyexplicit
• —Size: 1,018 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: 66.13 tokens</li><li>max: 248 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 76.82 tokens</li><li>max: 248 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 75.58 tokens</li><li>max: 251 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task037qascgeneraterelatedfact

• —Dataset: task037qascgeneraterelatedfact
• —Size: 1,018 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: 13 tokens</li><li>mean: 22.04 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 22.02 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 21.89 tokens</li><li>max: 40 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task027dropanswertypegeneration

• —Dataset: task027dropanswertypegeneration
• —Size: 1,018 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: 87 tokens</li><li>mean: 228.99 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 74 tokens</li><li>mean: 230.62 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 71 tokens</li><li>mean: 232.24 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1596event2mindtextgeneration2

• —Dataset: task1596event2mindtextgeneration2
• —Size: 1,018 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: 9.94 tokens</li><li>max: 18 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.01 tokens</li><li>max: 19 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 10.02 tokens</li><li>max: 18 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task141odd-man-outclassification_category

• —Dataset: task141odd-man-outclassification_category
• —Size: 1,018 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: 16 tokens</li><li>mean: 18.43 tokens</li><li>max: 28 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 18.37 tokens</li><li>max: 26 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 18.47 tokens</li><li>max: 25 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task194duorcanswer_generation

• —Dataset: task194duorcanswer_generation
• —Size: 1,018 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: 149 tokens</li><li>mean: 251.82 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 147 tokens</li><li>mean: 252.12 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 148 tokens</li><li>mean: 251.83 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task679hopeedienglishtext_classification

• —Dataset: task679hopeedienglishtext_classification
• —Size: 1,018 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: 27.83 tokens</li><li>max: 199 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 27.29 tokens</li><li>max: 205 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 29.94 tokens</li><li>max: 194 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task246dreamquestion_generation

• —Dataset: task246dreamquestion_generation
• —Size: 1,018 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: 17 tokens</li><li>mean: 80.17 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 81.39 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 87.22 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1195disflqadisfluenttofluent_conversion

• —Dataset: task1195disflqadisfluenttofluent_conversion
• —Size: 1,018 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: 19.77 tokens</li><li>max: 41 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 19.87 tokens</li><li>max: 40 tokens</li></ul> | <ul><li>min: 2 tokens</li><li>mean: 20.23 tokens</li><li>max: 44 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task065timetravelconsistentsentenceclassification

• —Dataset: task065timetravelconsistentsentenceclassification
• —Size: 1,018 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: 55 tokens</li><li>mean: 79.36 tokens</li><li>max: 117 tokens</li></ul> | <ul><li>min: 51 tokens</li><li>mean: 79.2 tokens</li><li>max: 110 tokens</li></ul> | <ul><li>min: 53 tokens</li><li>mean: 79.93 tokens</li><li>max: 110 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task351winomtclassificationgenderidentifiability_anti

• —Dataset: task351winomtclassificationgenderidentifiability_anti
• —Size: 1,018 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: 16 tokens</li><li>mean: 21.77 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.66 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.79 tokens</li><li>max: 30 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task580socialiqaanswer_generation

• —Dataset: task580socialiqaanswer_generation
• —Size: 1,018 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: 35 tokens</li><li>mean: 52.3 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: 50.9 tokens</li><li>max: 87 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task583udepsengcoarsepos_tagging

• —Dataset: task583udepsengcoarsepos_tagging
• —Size: 1,018 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: 41.2 tokens</li><li>max: 185 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.1 tokens</li><li>max: 185 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 40.88 tokens</li><li>max: 185 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task202mnlicontradiction_classification

• —Dataset: task202mnlicontradiction_classification
• —Size: 1,018 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: 24 tokens</li><li>mean: 73.76 tokens</li><li>max: 190 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 76.08 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 74.63 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task222rocstoriestwochioceslotting_classification

• —Dataset: task222rocstoriestwochioceslotting_classification
• —Size: 1,018 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: 48 tokens</li><li>mean: 73.1 tokens</li><li>max: 105 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 73.25 tokens</li><li>max: 100 tokens</li></ul> | <ul><li>min: 49 tokens</li><li>mean: 71.83 tokens</li><li>max: 102 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task498scruplesanecdoteswhoiswrongclassification

• —Dataset: task498scruplesanecdoteswhoiswrongclassification
• —Size: 1,018 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: 24 tokens</li><li>mean: 226.49 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 47 tokens</li><li>mean: 232.9 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 47 tokens</li><li>mean: 231.94 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task067abductivenlianswer_generation

• —Dataset: task067abductivenlianswer_generation
• —Size: 1,018 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: 14 tokens</li><li>mean: 26.68 tokens</li><li>max: 40 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 26.09 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 26.32 tokens</li><li>max: 38 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task616colaclassification

• —Dataset: task616colaclassification
• —Size: 1,018 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: 12.68 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 12.51 tokens</li><li>max: 33 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 12.4 tokens</li><li>max: 29 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task286olidoffense_judgment

• —Dataset: task286olidoffense_judgment
• —Size: 1,018 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: 32.65 tokens</li><li>max: 145 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 30.75 tokens</li><li>max: 171 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 30.25 tokens</li><li>max: 169 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task188snlineutraltoentailmenttextmodification

• —Dataset: task188snlineutraltoentailmenttextmodification
• —Size: 1,018 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: 18 tokens</li><li>mean: 31.75 tokens</li><li>max: 79 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 31.28 tokens</li><li>max: 84 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 32.97 tokens</li><li>max: 84 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task223quartzexplanation_generation

• —Dataset: task223quartzexplanation_generation
• —Size: 1,018 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: 31.53 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 31.86 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 28.89 tokens</li><li>max: 96 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task820protoqaanswer_generation

• —Dataset: task820protoqaanswer_generation
• —Size: 1,018 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: 14.54 tokens</li><li>max: 29 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 14.46 tokens</li><li>max: 27 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 14.07 tokens</li><li>max: 29 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task196sentiment140answer_generation

• —Dataset: task196sentiment140answer_generation
• —Size: 1,018 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: 17 tokens</li><li>mean: 36.07 tokens</li><li>max: 72 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 32.8 tokens</li><li>max: 61 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 36.08 tokens</li><li>max: 72 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1678mathqaanswer_selection

• —Dataset: task1678mathqaanswer_selection
• —Size: 1,018 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: 33 tokens</li><li>mean: 70.39 tokens</li><li>max: 177 tokens</li></ul> | <ul><li>min: 30 tokens</li><li>mean: 69.02 tokens</li><li>max: 146 tokens</li></ul> | <ul><li>min: 33 tokens</li><li>mean: 69.69 tokens</li><li>max: 160 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task349squad2.0answerableunanswerablequestion_classification

• —Dataset: task349squad2.0answerableunanswerablequestion_classification
• —Size: 1,018 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: 53 tokens</li><li>mean: 175.27 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 57 tokens</li><li>mean: 175.46 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 53 tokens</li><li>mean: 175.28 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task154tomqafindlocationhard_noise

• —Dataset: task154tomqafindlocationhard_noise
• —Size: 1,018 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: 129 tokens</li><li>mean: 176.58 tokens</li><li>max: 253 tokens</li></ul> | <ul><li>min: 126 tokens</li><li>mean: 176.32 tokens</li><li>max: 249 tokens</li></ul> | <ul><li>min: 128 tokens</li><li>mean: 178.35 tokens</li><li>max: 254 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task333hateevalclassificationhateen

• —Dataset: task333hateevalclassificationhateen
• —Size: 1,018 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: 38.52 tokens</li><li>max: 117 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 37.28 tokens</li><li>max: 109 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 36.88 tokens</li><li>max: 113 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task235iircquestionfromsubtextanswergeneration

• —Dataset: task235iircquestionfromsubtextanswergeneration
• —Size: 1,018 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: 14 tokens</li><li>mean: 52.76 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 50.84 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 55.7 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1554scitailclassification

• —Dataset: task1554scitailclassification
• —Size: 1,018 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: 16.81 tokens</li><li>max: 38 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 25.67 tokens</li><li>max: 68 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 24.35 tokens</li><li>max: 59 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task210logic2textstructuredtextgeneration

• —Dataset: task210logic2textstructuredtextgeneration
• —Size: 1,018 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: 13 tokens</li><li>mean: 31.73 tokens</li><li>max: 101 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 30.82 tokens</li><li>max: 94 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 32.82 tokens</li><li>max: 89 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task035winograndequestionmodificationperson

• —Dataset: task035winograndequestionmodificationperson
• —Size: 1,018 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: 31 tokens</li><li>mean: 36.18 tokens</li><li>max: 50 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 35.78 tokens</li><li>max: 55 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 35.43 tokens</li><li>max: 48 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task230iircpassage_classification

• —Dataset: task230iircpassage_classification
• —Size: 1,018 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: 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:

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

task1356xlsumtitle_generation

• —Dataset: task1356xlsumtitle_generation
• —Size: 1,018 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: 59 tokens</li><li>mean: 239.78 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 58 tokens</li><li>mean: 241.1 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 64 tokens</li><li>mean: 248.41 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task1726mathqacorrectanswergeneration

• —Dataset: task1726mathqacorrectanswergeneration
• —Size: 1,018 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: 43.66 tokens</li><li>max: 156 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 42.54 tokens</li><li>max: 129 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 42.63 tokens</li><li>max: 133 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task302recordclassification

• —Dataset: task302recordclassification
• —Size: 1,018 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: 194 tokens</li><li>mean: 253.52 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 198 tokens</li><li>mean: 253.15 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 195 tokens</li><li>mean: 252.97 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task380boolqyesnoquestion

• —Dataset: task380boolqyesnoquestion
• —Size: 1,018 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: 26 tokens</li><li>mean: 133.78 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 30 tokens</li><li>mean: 139.01 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 27 tokens</li><li>mean: 137.64 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task212logic2textclassification

• —Dataset: task212logic2textclassification
• —Size: 1,018 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: 14 tokens</li><li>mean: 32.95 tokens</li><li>max: 146 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 31.8 tokens</li><li>max: 146 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 32.68 tokens</li><li>max: 127 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task748glucosereversecauseevent_detection

• —Dataset: task748glucosereversecauseevent_detection
• —Size: 1,018 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: 35 tokens</li><li>mean: 67.7 tokens</li><li>max: 105 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 66.98 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 68.95 tokens</li><li>max: 105 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task834mathdatasetclassification

• —Dataset: task834mathdatasetclassification
• —Size: 1,018 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: 27.68 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 27.92 tokens</li><li>max: 83 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 27.06 tokens</li><li>max: 93 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task350winomtclassificationgenderidentifiability_pro

• —Dataset: task350winomtclassificationgenderidentifiability_pro
• —Size: 1,018 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: 16 tokens</li><li>mean: 21.83 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.64 tokens</li><li>max: 30 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 21.83 tokens</li><li>max: 30 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task191hotpotqaquestion_generation

• —Dataset: task191hotpotqaquestion_generation
• —Size: 1,018 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: 198 tokens</li><li>mean: 255.88 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 238 tokens</li><li>mean: 255.93 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:

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

task236iircquestionfrompassageanswergeneration

• —Dataset: task236iircquestionfrompassageanswergeneration
• —Size: 1,018 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: 135 tokens</li><li>mean: 238.65 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 155 tokens</li><li>mean: 237.61 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 154 tokens</li><li>mean: 239.64 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task217rocstoriesorderinganswergeneration

• —Dataset: task217rocstoriesorderinganswergeneration
• —Size: 1,018 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: 45 tokens</li><li>mean: 72.44 tokens</li><li>max: 107 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 72.32 tokens</li><li>max: 107 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 71.0 tokens</li><li>max: 105 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task568circaquestion_generation

• —Dataset: task568circaquestion_generation
• —Size: 1,018 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: 9.6 tokens</li><li>max: 25 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 9.46 tokens</li><li>max: 20 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 8.95 tokens</li><li>max: 20 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task614glucosecauseeventdetection

• —Dataset: task614glucosecauseeventdetection
• —Size: 1,018 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: 39 tokens</li><li>mean: 67.59 tokens</li><li>max: 102 tokens</li></ul> | <ul><li>min: 39 tokens</li><li>mean: 67.04 tokens</li><li>max: 106 tokens</li></ul> | <ul><li>min: 38 tokens</li><li>mean: 68.18 tokens</li><li>max: 103 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task361spolinyesandpromptresponse_classification

• —Dataset: task361spolinyesandpromptresponse_classification
• —Size: 1,018 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: 18 tokens</li><li>mean: 47.0 tokens</li><li>max: 137 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 46.18 tokens</li><li>max: 119 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 47.22 tokens</li><li>max: 128 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task421persentsentencesentimentclassification

• —Dataset: task421persentsentencesentimentclassification
• —Size: 1,018 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: 67.75 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 70.9 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 19 tokens</li><li>mean: 72.19 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task203mnlisentence_generation

• —Dataset: task203mnlisentence_generation
• —Size: 1,018 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: 14 tokens</li><li>mean: 38.63 tokens</li><li>max: 175 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 35.26 tokens</li><li>max: 175 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 34.05 tokens</li><li>max: 170 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

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

task420persentdocumentsentimentclassification

• —Dataset: task420persentdocumentsentimentclassification
• —Size: 1,018 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: 219.85 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 233.01 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 227.46 tokens</li><li>max: 256 tokens</li></ul> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters: