README.md

---
license: mit
size_categories:
- 100K<n<1M
pretty_name: n
dataset_info:
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    path: c10-16/186-*
  - split: '187'
    path: c10-16/187-*
  - split: '188'
    path: c10-16/188-*
  - split: '189'
    path: c10-16/189-*
  - split: '190'
    path: c10-16/190-*
  - split: '191'
    path: c10-16/191-*
  - split: '192'
    path: c10-16/192-*
  - split: '193'
    path: c10-16/193-*
  - split: '194'
    path: c10-16/194-*
  - split: '195'
    path: c10-16/195-*
  - split: '196'
    path: c10-16/196-*
  - split: '197'
    path: c10-16/197-*
  - split: '198'
    path: c10-16/198-*
  - split: '199'
    path: c10-16/199-*
  - split: '200'
    path: c10-16/200-*
  - split: '201'
    path: c10-16/201-*
  - split: '202'
    path: c10-16/202-*
  - split: '203'
    path: c10-16/203-*
  - split: '204'
    path: c10-16/204-*
  - split: '205'
    path: c10-16/205-*
  - split: '206'
    path: c10-16/206-*
  - split: '207'
    path: c10-16/207-*
  - split: '208'
    path: c10-16/208-*
  - split: '209'
    path: c10-16/209-*
  - split: '210'
    path: c10-16/210-*
  - split: '211'
    path: c10-16/211-*
  - split: '212'
    path: c10-16/212-*
  - split: '213'
    path: c10-16/213-*
  - split: '214'
    path: c10-16/214-*
  - split: '215'
    path: c10-16/215-*
  - split: '216'
    path: c10-16/216-*
  - split: '217'
    path: c10-16/217-*
  - split: '218'
    path: c10-16/218-*
  - split: '219'
    path: c10-16/219-*
  - split: '220'
    path: c10-16/220-*
  - split: '221'
    path: c10-16/221-*
  - split: '222'
    path: c10-16/222-*
  - split: '223'
    path: c10-16/223-*
  - split: '224'
    path: c10-16/224-*
  - split: '225'
    path: c10-16/225-*
  - split: '226'
    path: c10-16/226-*
  - split: '227'
    path: c10-16/227-*
  - split: '228'
    path: c10-16/228-*
  - split: '229'
    path: c10-16/229-*
  - split: '230'
    path: c10-16/230-*
  - split: '231'
    path: c10-16/231-*
  - split: '232'
    path: c10-16/232-*
  - split: '233'
    path: c10-16/233-*
  - split: '234'
    path: c10-16/234-*
  - split: '235'
    path: c10-16/235-*
  - split: '236'
    path: c10-16/236-*
  - split: '237'
    path: c10-16/237-*
  - split: '238'
    path: c10-16/238-*
  - split: '239'
    path: c10-16/239-*
  - split: '240'
    path: c10-16/240-*
  - split: '241'
    path: c10-16/241-*
  - split: '242'
    path: c10-16/242-*
  - split: '243'
    path: c10-16/243-*
  - split: '244'
    path: c10-16/244-*
  - split: '245'
    path: c10-16/245-*
  - split: '246'
    path: c10-16/246-*
  - split: '247'
    path: c10-16/247-*
  - split: '248'
    path: c10-16/248-*
  - split: '249'
    path: c10-16/249-*
  - split: '250'
    path: c10-16/250-*
  - split: '251'
    path: c10-16/251-*
  - split: '252'
    path: c10-16/252-*
  - split: '253'
    path: c10-16/253-*
  - split: '254'
    path: c10-16/254-*
  - split: '255'
    path: c10-16/255-*
  - split: '256'
    path: c10-16/256-*
  - split: '257'
    path: c10-16/257-*
  - split: '258'
    path: c10-16/258-*
  - split: '259'
    path: c10-16/259-*
  - split: '260'
    path: c10-16/260-*
  - split: '261'
    path: c10-16/261-*
  - split: '262'
    path: c10-16/262-*
  - split: '263'
    path: c10-16/263-*
  - split: '264'
    path: c10-16/264-*
  - split: '265'
    path: c10-16/265-*
  - split: '266'
    path: c10-16/266-*
  - split: '267'
    path: c10-16/267-*
  - split: '268'
    path: c10-16/268-*
  - split: '269'
    path: c10-16/269-*
  - split: '270'
    path: c10-16/270-*
  - split: '271'
    path: c10-16/271-*
  - split: '272'
    path: c10-16/272-*
  - split: '273'
    path: c10-16/273-*
  - split: '274'
    path: c10-16/274-*
  - split: '275'
    path: c10-16/275-*
  - split: '276'
    path: c10-16/276-*
  - split: '277'
    path: c10-16/277-*
  - split: '278'
    path: c10-16/278-*
  - split: '279'
    path: c10-16/279-*
  - split: '280'
    path: c10-16/280-*
  - split: '281'
    path: c10-16/281-*
  - split: '282'
    path: c10-16/282-*
  - split: '283'
    path: c10-16/283-*
  - split: '284'
    path: c10-16/284-*
  - split: '285'
    path: c10-16/285-*
  - split: '286'
    path: c10-16/286-*
  - split: '287'
    path: c10-16/287-*
  - split: '288'
    path: c10-16/288-*
  - split: '289'
    path: c10-16/289-*
  - split: '290'
    path: c10-16/290-*
  - split: '291'
    path: c10-16/291-*
  - split: '292'
    path: c10-16/292-*
  - split: '293'
    path: c10-16/293-*
  - split: '294'
    path: c10-16/294-*
  - split: '295'
    path: c10-16/295-*
  - split: '296'
    path: c10-16/296-*
  - split: '297'
    path: c10-16/297-*
  - split: '298'
    path: c10-16/298-*
  - split: '299'
    path: c10-16/299-*
- config_name: fm-16
  data_files:
  - split: '0'
    path: fm-16/0-*
  - split: '1'
    path: fm-16/1-*
  - split: '2'
    path: fm-16/2-*
  - split: '3'
    path: fm-16/3-*
  - split: '4'
    path: fm-16/4-*
  - split: '5'
    path: fm-16/5-*
  - split: '6'
    path: fm-16/6-*
  - split: '7'
    path: fm-16/7-*
  - split: '8'
    path: fm-16/8-*
  - split: '9'
    path: fm-16/9-*
  - split: '10'
    path: fm-16/10-*
  - split: '11'
    path: fm-16/11-*
  - split: '12'
    path: fm-16/12-*
  - split: '13'
    path: fm-16/13-*
  - split: '14'
    path: fm-16/14-*
  - split: '15'
    path: fm-16/15-*
  - split: '16'
    path: fm-16/16-*
  - split: '17'
    path: fm-16/17-*
  - split: '18'
    path: fm-16/18-*
  - split: '19'
    path: fm-16/19-*
  - split: '20'
    path: fm-16/20-*
  - split: '21'
    path: fm-16/21-*
  - split: '22'
    path: fm-16/22-*
  - split: '23'
    path: fm-16/23-*
  - split: '24'
    path: fm-16/24-*
  - split: '25'
    path: fm-16/25-*
  - split: '26'
    path: fm-16/26-*
  - split: '27'
    path: fm-16/27-*
  - split: '28'
    path: fm-16/28-*
  - split: '29'
    path: fm-16/29-*
  - split: '30'
    path: fm-16/30-*
  - split: '31'
    path: fm-16/31-*
  - split: '32'
    path: fm-16/32-*
  - split: '33'
    path: fm-16/33-*
  - split: '34'
    path: fm-16/34-*
  - split: '35'
    path: fm-16/35-*
  - split: '36'
    path: fm-16/36-*
  - split: '37'
    path: fm-16/37-*
  - split: '38'
    path: fm-16/38-*
  - split: '39'
    path: fm-16/39-*
  - split: '40'
    path: fm-16/40-*
  - split: '41'
    path: fm-16/41-*
  - split: '42'
    path: fm-16/42-*
  - split: '43'
    path: fm-16/43-*
  - split: '44'
    path: fm-16/44-*
  - split: '45'
    path: fm-16/45-*
  - split: '46'
    path: fm-16/46-*
  - split: '47'
    path: fm-16/47-*
  - split: '48'
    path: fm-16/48-*
  - split: '49'
    path: fm-16/49-*
  - split: '50'
    path: fm-16/50-*
  - split: '51'
    path: fm-16/51-*
  - split: '52'
    path: fm-16/52-*
  - split: '53'
    path: fm-16/53-*
  - split: '54'
    path: fm-16/54-*
  - split: '55'
    path: fm-16/55-*
  - split: '56'
    path: fm-16/56-*
  - split: '57'
    path: fm-16/57-*
  - split: '58'
    path: fm-16/58-*
  - split: '59'
    path: fm-16/59-*
  - split: '60'
    path: fm-16/60-*
  - split: '61'
    path: fm-16/61-*
  - split: '62'
    path: fm-16/62-*
  - split: '63'
    path: fm-16/63-*
  - split: '64'
    path: fm-16/64-*
  - split: '65'
    path: fm-16/65-*
  - split: '66'
    path: fm-16/66-*
  - split: '67'
    path: fm-16/67-*
  - split: '68'
    path: fm-16/68-*
  - split: '69'
    path: fm-16/69-*
  - split: '70'
    path: fm-16/70-*
  - split: '71'
    path: fm-16/71-*
  - split: '72'
    path: fm-16/72-*
  - split: '73'
    path: fm-16/73-*
  - split: '74'
    path: fm-16/74-*
  - split: '75'
    path: fm-16/75-*
  - split: '76'
    path: fm-16/76-*
  - split: '77'
    path: fm-16/77-*
  - split: '78'
    path: fm-16/78-*
  - split: '79'
    path: fm-16/79-*
  - split: '80'
    path: fm-16/80-*
  - split: '81'
    path: fm-16/81-*
  - split: '82'
    path: fm-16/82-*
  - split: '83'
    path: fm-16/83-*
  - split: '84'
    path: fm-16/84-*
  - split: '85'
    path: fm-16/85-*
  - split: '86'
    path: fm-16/86-*
  - split: '87'
    path: fm-16/87-*
  - split: '88'
    path: fm-16/88-*
  - split: '89'
    path: fm-16/89-*
  - split: '90'
    path: fm-16/90-*
  - split: '91'
    path: fm-16/91-*
  - split: '92'
    path: fm-16/92-*
  - split: '93'
    path: fm-16/93-*
  - split: '94'
    path: fm-16/94-*
  - split: '95'
    path: fm-16/95-*
  - split: '96'
    path: fm-16/96-*
  - split: '97'
    path: fm-16/97-*
  - split: '98'
    path: fm-16/98-*
  - split: '99'
    path: fm-16/99-*
  - split: '100'
    path: fm-16/100-*
  - split: '101'
    path: fm-16/101-*
  - split: '102'
    path: fm-16/102-*
  - split: '103'
    path: fm-16/103-*
  - split: '104'
    path: fm-16/104-*
  - split: '105'
    path: fm-16/105-*
  - split: '106'
    path: fm-16/106-*
  - split: '107'
    path: fm-16/107-*
  - split: '108'
    path: fm-16/108-*
  - split: '109'
    path: fm-16/109-*
  - split: '110'
    path: fm-16/110-*
  - split: '111'
    path: fm-16/111-*
  - split: '112'
    path: fm-16/112-*
  - split: '113'
    path: fm-16/113-*
  - split: '114'
    path: fm-16/114-*
  - split: '115'
    path: fm-16/115-*
  - split: '116'
    path: fm-16/116-*
  - split: '117'
    path: fm-16/117-*
  - split: '118'
    path: fm-16/118-*
  - split: '119'
    path: fm-16/119-*
  - split: '120'
    path: fm-16/120-*
  - split: '121'
    path: fm-16/121-*
  - split: '122'
    path: fm-16/122-*
  - split: '123'
    path: fm-16/123-*
  - split: '124'
    path: fm-16/124-*
  - split: '125'
    path: fm-16/125-*
  - split: '126'
    path: fm-16/126-*
  - split: '127'
    path: fm-16/127-*
  - split: '128'
    path: fm-16/128-*
  - split: '129'
    path: fm-16/129-*
  - split: '130'
    path: fm-16/130-*
  - split: '131'
    path: fm-16/131-*
  - split: '132'
    path: fm-16/132-*
  - split: '133'
    path: fm-16/133-*
  - split: '134'
    path: fm-16/134-*
  - split: '135'
    path: fm-16/135-*
  - split: '136'
    path: fm-16/136-*
  - split: '137'
    path: fm-16/137-*
  - split: '138'
    path: fm-16/138-*
  - split: '139'
    path: fm-16/139-*
  - split: '140'
    path: fm-16/140-*
  - split: '141'
    path: fm-16/141-*
  - split: '142'
    path: fm-16/142-*
  - split: '143'
    path: fm-16/143-*
  - split: '144'
    path: fm-16/144-*
  - split: '145'
    path: fm-16/145-*
  - split: '146'
    path: fm-16/146-*
  - split: '147'
    path: fm-16/147-*
  - split: '148'
    path: fm-16/148-*
  - split: '149'
    path: fm-16/149-*
  - split: '150'
    path: fm-16/150-*
  - split: '151'
    path: fm-16/151-*
  - split: '152'
    path: fm-16/152-*
  - split: '153'
    path: fm-16/153-*
  - split: '154'
    path: fm-16/154-*
  - split: '155'
    path: fm-16/155-*
  - split: '156'
    path: fm-16/156-*
  - split: '157'
    path: fm-16/157-*
  - split: '158'
    path: fm-16/158-*
  - split: '159'
    path: fm-16/159-*
  - split: '160'
    path: fm-16/160-*
  - split: '161'
    path: fm-16/161-*
  - split: '162'
    path: fm-16/162-*
  - split: '163'
    path: fm-16/163-*
  - split: '164'
    path: fm-16/164-*
  - split: '165'
    path: fm-16/165-*
  - split: '166'
    path: fm-16/166-*
  - split: '167'
    path: fm-16/167-*
  - split: '168'
    path: fm-16/168-*
  - split: '169'
    path: fm-16/169-*
  - split: '170'
    path: fm-16/170-*
  - split: '171'
    path: fm-16/171-*
  - split: '172'
    path: fm-16/172-*
  - split: '173'
    path: fm-16/173-*
  - split: '174'
    path: fm-16/174-*
  - split: '175'
    path: fm-16/175-*
  - split: '176'
    path: fm-16/176-*
  - split: '177'
    path: fm-16/177-*
  - split: '178'
    path: fm-16/178-*
  - split: '179'
    path: fm-16/179-*
  - split: '180'
    path: fm-16/180-*
  - split: '181'
    path: fm-16/181-*
  - split: '182'
    path: fm-16/182-*
  - split: '183'
    path: fm-16/183-*
  - split: '184'
    path: fm-16/184-*
  - split: '185'
    path: fm-16/185-*
  - split: '186'
    path: fm-16/186-*
  - split: '187'
    path: fm-16/187-*
  - split: '188'
    path: fm-16/188-*
  - split: '189'
    path: fm-16/189-*
  - split: '190'
    path: fm-16/190-*
  - split: '191'
    path: fm-16/191-*
  - split: '192'
    path: fm-16/192-*
  - split: '193'
    path: fm-16/193-*
  - split: '194'
    path: fm-16/194-*
  - split: '195'
    path: fm-16/195-*
  - split: '196'
    path: fm-16/196-*
  - split: '197'
    path: fm-16/197-*
  - split: '198'
    path: fm-16/198-*
  - split: '199'
    path: fm-16/199-*
  - split: '200'
    path: fm-16/200-*
  - split: '201'
    path: fm-16/201-*
  - split: '202'
    path: fm-16/202-*
  - split: '203'
    path: fm-16/203-*
  - split: '204'
    path: fm-16/204-*
  - split: '205'
    path: fm-16/205-*
  - split: '206'
    path: fm-16/206-*
  - split: '207'
    path: fm-16/207-*
  - split: '208'
    path: fm-16/208-*
  - split: '209'
    path: fm-16/209-*
  - split: '210'
    path: fm-16/210-*
  - split: '211'
    path: fm-16/211-*
  - split: '212'
    path: fm-16/212-*
  - split: '213'
    path: fm-16/213-*
  - split: '214'
    path: fm-16/214-*
  - split: '215'
    path: fm-16/215-*
  - split: '216'
    path: fm-16/216-*
  - split: '217'
    path: fm-16/217-*
  - split: '218'
    path: fm-16/218-*
  - split: '219'
    path: fm-16/219-*
  - split: '220'
    path: fm-16/220-*
  - split: '221'
    path: fm-16/221-*
  - split: '222'
    path: fm-16/222-*
  - split: '223'
    path: fm-16/223-*
  - split: '224'
    path: fm-16/224-*
  - split: '225'
    path: fm-16/225-*
  - split: '226'
    path: fm-16/226-*
  - split: '227'
    path: fm-16/227-*
  - split: '228'
    path: fm-16/228-*
  - split: '229'
    path: fm-16/229-*
  - split: '230'
    path: fm-16/230-*
  - split: '231'
    path: fm-16/231-*
  - split: '232'
    path: fm-16/232-*
  - split: '233'
    path: fm-16/233-*
  - split: '234'
    path: fm-16/234-*
  - split: '235'
    path: fm-16/235-*
  - split: '236'
    path: fm-16/236-*
  - split: '237'
    path: fm-16/237-*
  - split: '238'
    path: fm-16/238-*
  - split: '239'
    path: fm-16/239-*
  - split: '240'
    path: fm-16/240-*
  - split: '241'
    path: fm-16/241-*
  - split: '242'
    path: fm-16/242-*
  - split: '243'
    path: fm-16/243-*
  - split: '244'
    path: fm-16/244-*
  - split: '245'
    path: fm-16/245-*
  - split: '246'
    path: fm-16/246-*
  - split: '247'
    path: fm-16/247-*
  - split: '248'
    path: fm-16/248-*
  - split: '249'
    path: fm-16/249-*
  - split: '250'
    path: fm-16/250-*
  - split: '251'
    path: fm-16/251-*
  - split: '252'
    path: fm-16/252-*
  - split: '253'
    path: fm-16/253-*
  - split: '254'
    path: fm-16/254-*
  - split: '255'
    path: fm-16/255-*
  - split: '256'
    path: fm-16/256-*
  - split: '257'
    path: fm-16/257-*
  - split: '258'
    path: fm-16/258-*
  - split: '259'
    path: fm-16/259-*
  - split: '260'
    path: fm-16/260-*
  - split: '261'
    path: fm-16/261-*
  - split: '262'
    path: fm-16/262-*
  - split: '263'
    path: fm-16/263-*
  - split: '264'
    path: fm-16/264-*
  - split: '265'
    path: fm-16/265-*
  - split: '266'
    path: fm-16/266-*
  - split: '267'
    path: fm-16/267-*
  - split: '268'
    path: fm-16/268-*
  - split: '269'
    path: fm-16/269-*
  - split: '270'
    path: fm-16/270-*
  - split: '271'
    path: fm-16/271-*
  - split: '272'
    path: fm-16/272-*
  - split: '273'
    path: fm-16/273-*
  - split: '274'
    path: fm-16/274-*
  - split: '275'
    path: fm-16/275-*
  - split: '276'
    path: fm-16/276-*
  - split: '277'
    path: fm-16/277-*
  - split: '278'
    path: fm-16/278-*
  - split: '279'
    path: fm-16/279-*
  - split: '280'
    path: fm-16/280-*
  - split: '281'
    path: fm-16/281-*
  - split: '282'
    path: fm-16/282-*
  - split: '283'
    path: fm-16/283-*
  - split: '284'
    path: fm-16/284-*
  - split: '285'
    path: fm-16/285-*
  - split: '286'
    path: fm-16/286-*
  - split: '287'
    path: fm-16/287-*
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- config_name: lm1b-2-32
  data_files:
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- config_name: lm1b-3-24
  data_files:
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  - split: '71'
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  - split: '82'
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  - split: '83'
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  - split: '85'
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    path: lm1b-3-24/109-*
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    path: lm1b-3-24/110-*
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    path: lm1b-3-24/111-*
  - split: '112'
    path: lm1b-3-24/112-*
  - split: '113'
    path: lm1b-3-24/113-*
  - split: '114'
    path: lm1b-3-24/114-*
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---

This is the dataset of trained neural network checkpoints used to meta-train the NiNo model from https://github.com/SamsungSAILMontreal/nino/.

It contains 1000 models in total:
 - 300 small convnets with 3 layers and 16, 32 and 32 channels (14,378 parameters in each model), trained on FashionMNIST (**FM-16**)
 - 300 small convnets with 3 layers and 16, 32 and 32 channels (14,666 parameters in each model), trained on CIFAR10 (**C10-16**)
 - 200 small GPT2-based transformers with 3 layers, 24 hidden units and 3 heads (1,252,464 parameters in each model), trained on LM1B (**LM1B-3-24**)
 - 200 small GPT2-based transformers with 2 layers, 32 hidden units and 2 heads (1,666,464 parameters in each model), trained on LM1B (**LM1B-2-32**)

Each model contains multiple checkpoints:
 - 2688 checkpoints per each model in FM-16 (corresponding to every 4 steps of Adam)
 - 2513 checkpoints per each model in C10-16 (corresponding to every 4 steps of Adam)
 - 124 checkpoints per each model in LM1B-3-24 (corresponding to every 200 steps of Adam)
 - 124 checkpoints per each model in LM1B-2-32 (corresponding to every 200 steps of Adam)  

In total, there are 1,609,900 model checkpoints.

The dataset also contains the training loss for each checkpoint, for FM-16 and C10-16 it also contains training accuracy, test loss, test accuracy.

The dataset corresponds to the first 4 columns (in-distribution tasks) in Table 1 below.
<img src="https://cdn-uploads.huggingface.co/production/uploads/63e16165f0039731dfdd442a/GNPCk3RCZqsar_eTOo388.png" width="800">

This Table is from the `Accelerating Training with Neuron Interaction and Nowcasting Networks` paper, see https://arxiv.org/abs/2409.04434 for details.

# Example

**UPDATE: To train the NiNo model more efficiently we also uploaded the dataset in the mmap format (in the mmap branch), which is much faster to read for large arrays.
See https://github.com/SamsungSAILMontreal/nino/blob/main/dataset/dataset.py#L123 for the dataset code 
and https://github.com/SamsungSAILMontreal/nino/blob/main/README.md#training-nino for the training script examples.**


Download and access trajectories of the fm-16 task (other three datasets: 'c10-16', 'lm1b-3-24', 'lm1b-2-32').
The original trajectories was saved as float16, but when loading huggingface may convert it to float32 or float64 depending on the version.

```python
from datasets import load_dataset
import numpy as np

# Load the 'fm-16' task
dataset = load_dataset('SamsungSAILMontreal/nino_metatrain', 'fm-16')  # you can use streaming=True for checking out individual samples

# Once downloaded, access the t-th state in the i-th trajectory: 
print(np.array(dataset[str(i)][t]['data']).shape)  # (14378,)

```