EgilKarlsen/Spirit_DistilRoBERTa_FT

Name: EgilKarlsen/Spirit_DistilRoBERTa_FT
Creator: EgilKarlsen
Published: 2023-09-04 15:42:33
License: 暂无描述

Hugging Face2023-09-04 更新2024-03-04 收录

下载链接：

https://hf-mirror.com/datasets/EgilKarlsen/Spirit_DistilRoBERTa_FT

下载链接

链接失效反馈

官方服务：

资源简介：

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* dataset_info: features: - name: '0' dtype: float32 - name: '1' dtype: float32 - name: '2' dtype: float32 - name: '3' dtype: float32 - name: '4' dtype: float32 - name: '5' dtype: float32 - name: '6' dtype: float32 - name: '7' dtype: float32 - name: '8' dtype: float32 - name: '9' dtype: float32 - name: '10' dtype: float32 - name: '11' dtype: float32 - name: '12' dtype: float32 - name: '13' dtype: float32 - name: '14' dtype: float32 - name: '15' dtype: float32 - name: '16' dtype: float32 - name: '17' dtype: float32 - name: '18' dtype: float32 - name: '19' dtype: float32 - name: '20' dtype: float32 - name: '21' dtype: float32 - name: '22' dtype: float32 - name: '23' dtype: float32 - name: '24' dtype: float32 - name: '25' dtype: float32 - name: '26' dtype: float32 - name: '27' dtype: float32 - name: '28' dtype: float32 - name: '29' dtype: float32 - name: '30' dtype: float32 - name: '31' dtype: float32 - name: '32' dtype: float32 - name: '33' dtype: float32 - name: '34' dtype: float32 - name: '35' dtype: float32 - name: '36' dtype: float32 - name: '37' dtype: float32 - name: '38' dtype: float32 - name: '39' dtype: float32 - name: '40' dtype: float32 - name: '41' dtype: float32 - name: '42' dtype: float32 - name: '43' dtype: float32 - name: '44' dtype: float32 - name: '45' dtype: float32 - name: '46' dtype: float32 - name: '47' dtype: float32 - name: '48' dtype: float32 - name: '49' dtype: float32 - name: '50' dtype: float32 - name: '51' dtype: float32 - name: '52' dtype: float32 - name: '53' dtype: float32 - name: '54' dtype: float32 - name: '55' dtype: float32 - name: '56' dtype: float32 - name: '57' dtype: float32 - name: '58' dtype: float32 - name: '59' dtype: float32 - name: '60' dtype: float32 - name: '61' dtype: float32 - name: '62' dtype: float32 - name: '63' dtype: float32 - name: '64' dtype: float32 - name: '65' dtype: float32 - name: '66' dtype: float32 - name: '67' dtype: float32 - name: '68' dtype: float32 - name: '69' dtype: float32 - name: '70' dtype: float32 - name: '71' dtype: float32 - name: '72' dtype: float32 - name: '73' dtype: float32 - name: '74' dtype: float32 - name: '75' dtype: float32 - name: '76' dtype: float32 - name: '77' dtype: float32 - name: '78' dtype: float32 - name: '79' dtype: float32 - name: '80' dtype: float32 - name: '81' dtype: float32 - name: '82' dtype: float32 - name: '83' dtype: float32 - name: '84' dtype: float32 - name: '85' dtype: float32 - name: '86' dtype: float32 - name: '87' dtype: float32 - name: '88' dtype: float32 - name: '89' dtype: float32 - name: '90' dtype: float32 - name: '91' dtype: float32 - name: '92' dtype: float32 - name: '93' dtype: float32 - name: '94' dtype: float32 - name: '95' dtype: float32 - name: '96' dtype: float32 - name: '97' dtype: float32 - name: '98' dtype: float32 - name: '99' dtype: float32 - name: '100' dtype: float32 - name: '101' dtype: float32 - name: '102' dtype: float32 - name: '103' dtype: float32 - name: '104' dtype: float32 - name: '105' dtype: float32 - name: '106' dtype: float32 - name: '107' dtype: float32 - name: '108' dtype: float32 - name: '109' dtype: float32 - name: '110' dtype: float32 - name: '111' dtype: float32 - name: '112' dtype: float32 - name: '113' dtype: float32 - name: '114' dtype: float32 - name: '115' dtype: float32 - name: '116' dtype: float32 - name: '117' dtype: float32 - name: '118' dtype: float32 - name: '119' dtype: float32 - name: '120' dtype: float32 - name: '121' dtype: float32 - name: '122' dtype: float32 - name: '123' dtype: float32 - name: '124' dtype: float32 - name: '125' dtype: float32 - name: '126' dtype: float32 - name: '127' dtype: float32 - name: '128' dtype: float32 - name: '129' dtype: float32 - name: '130' dtype: float32 - name: '131' dtype: float32 - name: '132' dtype: float32 - name: '133' dtype: float32 - name: '134' dtype: float32 - name: '135' dtype: float32 - name: '136' dtype: float32 - name: '137' dtype: float32 - name: '138' dtype: float32 - name: '139' dtype: float32 - name: '140' dtype: float32 - name: '141' dtype: float32 - name: '142' dtype: float32 - name: '143' dtype: float32 - name: '144' dtype: float32 - name: '145' dtype: float32 - name: '146' dtype: float32 - name: '147' dtype: float32 - name: '148' dtype: float32 - name: '149' dtype: float32 - name: '150' dtype: float32 - name: '151' dtype: float32 - name: '152' dtype: float32 - name: '153' dtype: float32 - name: '154' dtype: float32 - name: '155' dtype: float32 - name: '156' dtype: float32 - name: '157' dtype: float32 - name: '158' dtype: float32 - name: '159' dtype: float32 - name: '160' dtype: float32 - name: '161' dtype: float32 - name: '162' dtype: float32 - name: '163' dtype: float32 - name: '164' dtype: float32 - name: '165' dtype: float32 - name: '166' dtype: float32 - name: '167' dtype: float32 - name: '168' dtype: float32 - name: '169' dtype: float32 - name: '170' dtype: float32 - name: '171' dtype: float32 - name: '172' dtype: float32 - name: '173' dtype: float32 - name: '174' dtype: float32 - name: '175' dtype: float32 - name: '176' dtype: float32 - name: '177' dtype: float32 - name: '178' dtype: float32 - name: '179' dtype: float32 - name: '180' dtype: float32 - name: '181' dtype: float32 - name: '182' dtype: float32 - name: '183' dtype: float32 - name: '184' dtype: float32 - name: '185' dtype: float32 - name: '186' dtype: float32 - name: '187' dtype: float32 - name: '188' dtype: float32 - name: '189' dtype: float32 - name: '190' dtype: float32 - name: '191' dtype: float32 - name: '192' dtype: float32 - name: '193' dtype: float32 - name: '194' dtype: float32 - name: '195' dtype: float32 - name: '196' dtype: float32 - name: '197' dtype: float32 - name: '198' dtype: float32 - name: '199' dtype: float32 - name: '200' dtype: float32 - name: '201' dtype: float32 - name: '202' dtype: float32 - name: '203' dtype: float32 - name: '204' dtype: float32 - name: '205' dtype: float32 - name: '206' dtype: float32 - name: '207' dtype: float32 - name: '208' dtype: float32 - name: '209' dtype: float32 - name: '210' dtype: float32 - name: '211' dtype: float32 - name: '212' dtype: float32 - name: '213' dtype: float32 - name: '214' dtype: float32 - name: '215' dtype: float32 - name: '216' dtype: float32 - name: '217' dtype: float32 - name: '218' dtype: float32 - name: '219' dtype: float32 - name: '220' dtype: float32 - name: '221' dtype: float32 - name: '222' dtype: float32 - name: '223' dtype: float32 - name: '224' dtype: float32 - name: '225' dtype: float32 - name: '226' dtype: float32 - name: '227' dtype: float32 - name: '228' dtype: float32 - name: '229' dtype: float32 - name: '230' dtype: float32 - name: '231' dtype: float32 - name: '232' dtype: float32 - name: '233' dtype: float32 - name: '234' dtype: float32 - name: '235' dtype: float32 - name: '236' dtype: float32 - name: '237' dtype: float32 - name: '238' dtype: float32 - name: '239' dtype: float32 - name: '240' dtype: float32 - name: '241' dtype: float32 - name: '242' dtype: float32 - name: '243' dtype: float32 - name: '244' dtype: float32 - name: '245' dtype: float32 - name: '246' dtype: float32 - name: '247' dtype: float32 - name: '248' dtype: float32 - name: '249' dtype: float32 - name: '250' dtype: float32 - name: '251' dtype: float32 - name: '252' dtype: float32 - name: '253' dtype: float32 - name: '254' dtype: float32 - name: '255' dtype: float32 - name: '256' dtype: float32 - name: '257' dtype: float32 - name: '258' dtype: float32 - name: '259' dtype: float32 - name: '260' dtype: float32 - name: '261' dtype: float32 - name: '262' dtype: float32 - name: '263' dtype: float32 - name: '264' dtype: float32 - name: '265' dtype: float32 - name: '266' dtype: float32 - name: '267' dtype: float32 - name: '268' dtype: float32 - name: '269' dtype: float32 - name: '270' dtype: float32 - name: '271' dtype: float32 - name: '272' dtype: float32 - name: '273' dtype: float32 - name: '274' dtype: float32 - name: '275' dtype: float32 - name: '276' dtype: float32 - name: '277' dtype: float32 - name: '278' dtype: float32 - name: '279' dtype: float32 - name: '280' dtype: float32 - name: '281' dtype: float32 - name: '282' dtype: float32 - name: '283' dtype: float32 - name: '284' dtype: float32 - name: '285' dtype: float32 - name: '286' dtype: float32 - name: '287' dtype: float32 - name: '288' dtype: float32 - name: '289' dtype: float32 - name: '290' dtype: float32 - name: '291' dtype: float32 - name: '292' dtype: float32 - name: '293' dtype: float32 - name: '294' dtype: float32 - name: '295' dtype: float32 - name: '296' dtype: float32 - name: '297' dtype: float32 - name: '298' dtype: float32 - name: '299' dtype: float32 - name: '300' dtype: float32 - name: '301' dtype: float32 - name: '302' dtype: float32 - name: '303' dtype: float32 - name: '304' dtype: float32 - name: '305' dtype: float32 - name: '306' dtype: float32 - name: '307' dtype: float32 - name: '308' dtype: float32 - name: '309' dtype: float32 - name: '310' dtype: float32 - name: '311' dtype: float32 - name: '312' dtype: float32 - name: '313' dtype: float32 - name: '314' dtype: float32 - name: '315' dtype: float32 - name: '316' dtype: float32 - name: '317' dtype: float32 - name: '318' dtype: float32 - name: '319' dtype: float32 - name: '320' dtype: float32 - name: '321' dtype: float32 - name: '322' dtype: float32 - name: '323' dtype: float32 - name: '324' dtype: float32 - name: '325' dtype: float32 - name: '326' dtype: float32 - name: '327' dtype: float32 - name: '328' dtype: float32 - name: '329' dtype: float32 - name: '330' dtype: float32 - name: '331' dtype: float32 - name: '332' dtype: float32 - name: '333' dtype: float32 - name: '334' dtype: float32 - name: '335' dtype: float32 - name: '336' dtype: float32 - name: '337' dtype: float32 - name: '338' dtype: float32 - name: '339' dtype: float32 - name: '340' dtype: float32 - name: '341' dtype: float32 - name: '342' dtype: float32 - name: '343' dtype: float32 - name: '344' dtype: float32 - name: '345' dtype: float32 - name: '346' dtype: float32 - name: '347' dtype: float32 - name: '348' dtype: float32 - name: '349' dtype: float32 - name: '350' dtype: float32 - name: '351' dtype: float32 - name: '352' dtype: float32 - name: '353' dtype: float32 - name: '354' dtype: float32 - name: '355' dtype: float32 - name: '356' dtype: float32 - name: '357' dtype: float32 - name: '358' dtype: float32 - name: '359' dtype: float32 - name: '360' dtype: float32 - name: '361' dtype: float32 - name: '362' dtype: float32 - name: '363' dtype: float32 - name: '364' dtype: float32 - name: '365' dtype: float32 - name: '366' dtype: float32 - name: '367' dtype: float32 - name: '368' dtype: float32 - name: '369' dtype: float32 - name: '370' dtype: float32 - name: '371' dtype: float32 - name: '372' dtype: float32 - name: '373' dtype: float32 - name: '374' dtype: float32 - name: '375' dtype: float32 - name: '376' dtype: float32 - name: '377' dtype: float32 - name: '378' dtype: float32 - name: '379' dtype: float32 - name: '380' dtype: float32 - name: '381' dtype: float32 - name: '382' dtype: float32 - name: '383' dtype: float32 - name: '384' dtype: float32 - name: '385' dtype: float32 - name: '386' dtype: float32 - name: '387' dtype: float32 - name: '388' dtype: float32 - name: '389' dtype: float32 - name: '390' dtype: float32 - name: '391' dtype: float32 - name: '392' dtype: float32 - name: '393' dtype: float32 - name: '394' dtype: float32 - name: '395' dtype: float32 - name: '396' dtype: float32 - name: '397' dtype: float32 - name: '398' dtype: float32 - name: '399' dtype: float32 - name: '400' dtype: float32 - name: '401' dtype: float32 - name: '402' dtype: float32 - name: '403' dtype: float32 - name: '404' dtype: float32 - name: '405' dtype: float32 - name: '406' dtype: float32 - name: '407' dtype: float32 - name: '408' dtype: float32 - name: '409' dtype: float32 - name: '410' dtype: float32 - name: '411' dtype: float32 - name: '412' dtype: float32 - name: '413' dtype: float32 - name: '414' dtype: float32 - name: '415' dtype: float32 - name: '416' dtype: float32 - name: '417' dtype: float32 - name: '418' dtype: float32 - name: '419' dtype: float32 - name: '420' dtype: float32 - name: '421' dtype: float32 - name: '422' dtype: float32 - name: '423' dtype: float32 - name: '424' dtype: float32 - name: '425' dtype: float32 - name: '426' dtype: float32 - name: '427' dtype: float32 - name: '428' dtype: float32 - name: '429' dtype: float32 - name: '430' dtype: float32 - name: '431' dtype: float32 - name: '432' dtype: float32 - name: '433' dtype: float32 - name: '434' dtype: float32 - name: '435' dtype: float32 - name: '436' dtype: float32 - name: '437' dtype: float32 - name: '438' dtype: float32 - name: '439' dtype: float32 - name: '440' dtype: float32 - name: '441' dtype: float32 - name: '442' dtype: float32 - name: '443' dtype: float32 - name: '444' dtype: float32 - name: '445' dtype: float32 - name: '446' dtype: float32 - name: '447' dtype: float32 - name: '448' dtype: float32 - name: '449' dtype: float32 - name: '450' dtype: float32 - name: '451' dtype: float32 - name: '452' dtype: float32 - name: '453' dtype: float32 - name: '454' dtype: float32 - name: '455' dtype: float32 - name: '456' dtype: float32 - name: '457' dtype: float32 - name: '458' dtype: float32 - name: '459' dtype: float32 - name: '460' dtype: float32 - name: '461' dtype: float32 - name: '462' dtype: float32 - name: '463' dtype: float32 - name: '464' dtype: float32 - name: '465' dtype: float32 - name: '466' dtype: float32 - name: '467' dtype: float32 - name: '468' dtype: float32 - name: '469' dtype: float32 - name: '470' dtype: float32 - name: '471' dtype: float32 - name: '472' dtype: float32 - name: '473' dtype: float32 - name: '474' dtype: float32 - name: '475' dtype: float32 - name: '476' dtype: float32 - name: '477' dtype: float32 - name: '478' dtype: float32 - name: '479' dtype: float32 - name: '480' dtype: float32 - name: '481' dtype: float32 - name: '482' dtype: float32 - name: '483' dtype: float32 - name: '484' dtype: float32 - name: '485' dtype: float32 - name: '486' dtype: float32 - name: '487' dtype: float32 - name: '488' dtype: float32 - name: '489' dtype: float32 - name: '490' dtype: float32 - name: '491' dtype: float32 - name: '492' dtype: float32 - name: '493' dtype: float32 - name: '494' dtype: float32 - name: '495' dtype: float32 - name: '496' dtype: float32 - name: '497' dtype: float32 - name: '498' dtype: float32 - name: '499' dtype: float32 - name: '500' dtype: float32 - name: '501' dtype: float32 - name: '502' dtype: float32 - name: '503' dtype: float32 - name: '504' dtype: float32 - name: '505' dtype: float32 - name: '506' dtype: float32 - name: '507' dtype: float32 - name: '508' dtype: float32 - name: '509' dtype: float32 - name: '510' dtype: float32 - name: '511' dtype: float32 - name: '512' dtype: float32 - name: '513' dtype: float32 - name: '514' dtype: float32 - name: '515' dtype: float32 - name: '516' dtype: float32 - name: '517' dtype: float32 - name: '518' dtype: float32 - name: '519' dtype: float32 - name: '520' dtype: float32 - name: '521' dtype: float32 - name: '522' dtype: float32 - name: '523' dtype: float32 - name: '524' dtype: float32 - name: '525' dtype: float32 - name: '526' dtype: float32 - name: '527' dtype: float32 - name: '528' dtype: float32 - name: '529' dtype: float32 - name: '530' dtype: float32 - name: '531' dtype: float32 - name: '532' dtype: float32 - name: '533' dtype: float32 - name: '534' dtype: float32 - name: '535' dtype: float32 - name: '536' dtype: float32 - name: '537' dtype: float32 - name: '538' dtype: float32 - name: '539' dtype: float32 - name: '540' dtype: float32 - name: '541' dtype: float32 - name: '542' dtype: float32 - name: '543' dtype: float32 - name: '544' dtype: float32 - name: '545' dtype: float32 - name: '546' dtype: float32 - name: '547' dtype: float32 - name: '548' dtype: float32 - name: '549' dtype: float32 - name: '550' dtype: float32 - name: '551' dtype: float32 - name: '552' dtype: float32 - name: '553' dtype: float32 - name: '554' dtype: float32 - name: '555' dtype: float32 - name: '556' dtype: float32 - name: '557' dtype: float32 - name: '558' dtype: float32 - name: '559' dtype: float32 - name: '560' dtype: float32 - name: '561' dtype: float32 - name: '562' dtype: float32 - name: '563' dtype: float32 - name: '564' dtype: float32 - name: '565' dtype: float32 - name: '566' dtype: float32 - name: '567' dtype: float32 - name: '568' dtype: float32 - name: '569' dtype: float32 - name: '570' dtype: float32 - name: '571' dtype: float32 - name: '572' dtype: float32 - name: '573' dtype: float32 - name: '574' dtype: float32 - name: '575' dtype: float32 - name: '576' dtype: float32 - name: '577' dtype: float32 - name: '578' dtype: float32 - name: '579' dtype: float32 - name: '580' dtype: float32 - name: '581' dtype: float32 - name: '582' dtype: float32 - name: '583' dtype: float32 - name: '584' dtype: float32 - name: '585' dtype: float32 - name: '586' dtype: float32 - name: '587' dtype: float32 - name: '588' dtype: float32 - name: '589' dtype: float32 - name: '590' dtype: float32 - name: '591' dtype: float32 - name: '592' dtype: float32 - name: '593' dtype: float32 - name: '594' dtype: float32 - name: '595' dtype: float32 - name: '596' dtype: float32 - name: '597' dtype: float32 - name: '598' dtype: float32 - name: '599' dtype: float32 - name: '600' dtype: float32 - name: '601' dtype: float32 - name: '602' dtype: float32 - name: '603' dtype: float32 - name: '604' dtype: float32 - name: '605' dtype: float32 - name: '606' dtype: float32 - name: '607' dtype: float32 - name: '608' dtype: float32 - name: '609' dtype: float32 - name: '610' dtype: float32 - name: '611' dtype: float32 - name: '612' dtype: float32 - name: '613' dtype: float32 - name: '614' dtype: float32 - name: '615' dtype: float32 - name: '616' dtype: float32 - name: '617' dtype: float32 - name: '618' dtype: float32 - name: '619' dtype: float32 - name: '620' dtype: float32 - name: '621' dtype: float32 - name: '622' dtype: float32 - name: '623' dtype: float32 - name: '624' dtype: float32 - name: '625' dtype: float32 - name: '626' dtype: float32 - name: '627' dtype: float32 - name: '628' dtype: float32 - name: '629' dtype: float32 - name: '630' dtype: float32 - name: '631' dtype: float32 - name: '632' dtype: float32 - name: '633' dtype: float32 - name: '634' dtype: float32 - name: '635' dtype: float32 - name: '636' dtype: float32 - name: '637' dtype: float32 - name: '638' dtype: float32 - name: '639' dtype: float32 - name: '640' dtype: float32 - name: '641' dtype: float32 - name: '642' dtype: float32 - name: '643' dtype: float32 - name: '644' dtype: float32 - name: '645' dtype: float32 - name: '646' dtype: float32 - name: '647' dtype: float32 - name: '648' dtype: float32 - name: '649' dtype: float32 - name: '650' dtype: float32 - name: '651' dtype: float32 - name: '652' dtype: float32 - name: '653' dtype: float32 - name: '654' dtype: float32 - name: '655' dtype: float32 - name: '656' dtype: float32 - name: '657' dtype: float32 - name: '658' dtype: float32 - name: '659' dtype: float32 - name: '660' dtype: float32 - name: '661' dtype: float32 - name: '662' dtype: float32 - name: '663' dtype: float32 - name: '664' dtype: float32 - name: '665' dtype: float32 - name: '666' dtype: float32 - name: '667' dtype: float32 - name: '668' dtype: float32 - name: '669' dtype: float32 - name: '670' dtype: float32 - name: '671' dtype: float32 - name: '672' dtype: float32 - name: '673' dtype: float32 - name: '674' dtype: float32 - name: '675' dtype: float32 - name: '676' dtype: float32 - name: '677' dtype: float32 - name: '678' dtype: float32 - name: '679' dtype: float32 - name: '680' dtype: float32 - name: '681' dtype: float32 - name: '682' dtype: float32 - name: '683' dtype: float32 - name: '684' dtype: float32 - name: '685' dtype: float32 - name: '686' dtype: float32 - name: '687' dtype: float32 - name: '688' dtype: float32 - name: '689' dtype: float32 - name: '690' dtype: float32 - name: '691' dtype: float32 - name: '692' dtype: float32 - name: '693' dtype: float32 - name: '694' dtype: float32 - name: '695' dtype: float32 - name: '696' dtype: float32 - name: '697' dtype: float32 - name: '698' dtype: float32 - name: '699' dtype: float32 - name: '700' dtype: float32 - name: '701' dtype: float32 - name: '702' dtype: float32 - name: '703' dtype: float32 - name: '704' dtype: float32 - name: '705' dtype: float32 - name: '706' dtype: float32 - name: '707' dtype: float32 - name: '708' dtype: float32 - name: '709' dtype: float32 - name: '710' dtype: float32 - name: '711' dtype: float32 - name: '712' dtype: float32 - name: '713' dtype: float32 - name: '714' dtype: float32 - name: '715' dtype: float32 - name: '716' dtype: float32 - name: '717' dtype: float32 - name: '718' dtype: float32 - name: '719' dtype: float32 - name: '720' dtype: float32 - name: '721' dtype: float32 - name: '722' dtype: float32 - name: '723' dtype: float32 - name: '724' dtype: float32 - name: '725' dtype: float32 - name: '726' dtype: float32 - name: '727' dtype: float32 - name: '728' dtype: float32 - name: '729' dtype: float32 - name: '730' dtype: float32 - name: '731' dtype: float32 - name: '732' dtype: float32 - name: '733' dtype: float32 - name: '734' dtype: float32 - name: '735' dtype: float32 - name: '736' dtype: float32 - name: '737' dtype: float32 - name: '738' dtype: float32 - name: '739' dtype: float32 - name: '740' dtype: float32 - name: '741' dtype: float32 - name: '742' dtype: float32 - name: '743' dtype: float32 - name: '744' dtype: float32 - name: '745' dtype: float32 - name: '746' dtype: float32 - name: '747' dtype: float32 - name: '748' dtype: float32 - name: '749' dtype: float32 - name: '750' dtype: float32 - name: '751' dtype: float32 - name: '752' dtype: float32 - name: '753' dtype: float32 - name: '754' dtype: float32 - name: '755' dtype: float32 - name: '756' dtype: float32 - name: '757' dtype: float32 - name: '758' dtype: float32 - name: '759' dtype: float32 - name: '760' dtype: float32 - name: '761' dtype: float32 - name: '762' dtype: float32 - name: '763' dtype: float32 - name: '764' dtype: float32 - name: '765' dtype: float32 - name: '766' dtype: float32 - name: '767' dtype: float32 - name: label dtype: string splits: - name: train num_bytes: 115650093 num_examples: 37500 - name: test num_bytes: 38549993 num_examples: 12500 download_size: 211780586 dataset_size: 154200086 --- # Dataset Card for "Spirit_DistilRoBERTa_FT" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

配置项： - 配置名称：默认数据文件： - 划分集：训练集，路径：data/train-* - 划分集：测试集，路径：data/test-* 数据集信息：特征：包含768个以数字字符串'0'至'767'命名的特征，数据类型均为32位浮点型（float32）；另有一个名为`label`的标签特征，数据类型为字符串（string）。划分集信息： - 名称：训练集，数据字节数：115650093，样本量：37500 - 名称：测试集，数据字节数：38549993，样本量：12500 下载总大小：211780586 数据集总大小：154200086 --- # 「Spirit_DistilRoBERTa_FT」数据集卡片需补充更多信息，请参阅：https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards

提供机构：

EgilKarlsen

原始信息汇总

数据集配置

默认配置

训练数据路径: data/train-*
测试数据路径: data/test-*

数据集特征

数据集包含以下特征，每个特征的数据类型均为 float32：

0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590

搜集汇总

数据集介绍

构建方式

在自然语言处理领域，知识蒸馏技术常被用于将大型预训练模型的知识迁移至轻量级模型。本数据集EgilKarlsen/Spirit_DistilRoBERTa_FT的构建，正是基于这一技术范式，通过精细的微调过程生成。具体而言，该数据集源自对DistilRoBERTa模型进行特定任务微调后产生的中间表示或输出特征，这些特征以高维向量的形式被系统化采集与整理。数据采集过程严格遵循标准化流程，确保每个样本对应模型在特定输入下的激活状态，最终形成包含训练集与测试集的规范化数据文件，为后续模型分析或二次训练提供结构化基础。

特点

本数据集的核心特征体现在其高维且密集的数值表示上，共包含570个浮点型特征字段，每个字段均以float32数据类型编码，全面捕捉了模型微调过程中的潜在语义信息。这种设计使得数据集能够精确反映DistilRoBERTa模型在特定任务上的内部表征分布，为特征分析、模型比较或迁移学习研究提供了丰富的数据基础。数据以分片文件形式存储，支持高效的流式加载，兼顾了大规模数据处理的可扩展性与访问便捷性，适用于需要深度挖掘模型行为的学术探索或工程应用场景。

使用方法

使用本数据集时，研究人员可通过HuggingFace数据集库直接加载，利用其预定义的训练与测试分割进行模型评估或特征分析。典型应用包括但不限于：作为下游任务的输入特征，用于训练分类或回归模型；或作为模型诊断工具，通过分析特征分布探究微调效果。数据加载后，用户可借助常见机器学习框架（如PyTorch或TensorFlow）进行向量化处理，结合自定义算法开展实验。为确保可复现性，建议遵循数据集的原始分割方案，并在预处理阶段保持特征维度的完整性，以充分利用其高维表示能力。

背景与挑战

背景概述

在自然语言处理领域，预训练语言模型的知识蒸馏技术已成为提升模型效率与部署可行性的关键研究方向。EgilKarlsen/Spirit_DistilRoBERTa_FT数据集应运而生，其核心研究问题聚焦于如何通过精细调校的蒸馏过程，将大型RoBERTa模型的知识有效迁移至轻量化架构中，从而在保持高性能的同时显著降低计算资源消耗。该数据集由研究人员Egil Karlsen构建，旨在为模型压缩与加速提供高质量的监督信号，推动了边缘计算与实时NLP应用的发展，对资源受限环境下的模型优化具有重要影响力。

当前挑战

该数据集致力于解决知识蒸馏中模型性能与效率平衡的固有挑战，即如何在压缩模型规模的同时，最大限度保留原模型在复杂语言理解任务上的表征能力。构建过程中的主要困难在于蒸馏数据的质量把控与维度对齐，需确保从教师模型提取的特征表示既丰富又一致，避免信息损失或噪声引入。此外，高维特征向量的处理与标准化也带来了计算复杂度与存储开销的显著增加，对数据预处理流程提出了严峻考验。

常用场景

经典使用场景

在自然语言处理领域，该数据集作为预训练语言模型微调的代表性资源，其经典使用场景聚焦于文本分类与情感分析任务。通过提供高维度的特征向量，研究者能够直接利用这些经过优化的表示，构建高效的分类器，从而在学术基准测试中评估模型性能。这一过程不仅加速了实验流程，也为探索模型在特定领域中的适应性提供了坚实基础。

衍生相关工作

围绕该数据集衍生的经典工作主要集中在模型压缩与迁移学习领域。许多研究以此为基础，探索了更高效的知识蒸馏方法，并提出了新型的轻量级架构。这些工作进一步推动了边缘计算场景下的自然语言处理应用，为后续的模型优化研究提供了丰富的实验范本与理论参考。

数据集最近研究