metadata

base_model: sentence-transformers/paraphrase-MiniLM-L3-v2
library_name: setfit
metrics:
  - accuracy
pipeline_tag: text-classification
tags:
  - setfit
  - sentence-transformers
  - text-classification
  - generated_from_setfit_trainer
widget:
  - text: >-
      metrics.statistics.polysyllables: 4603, 102, 339, 2604, 397, 1180, 555,
      1488, 1226, 378, 6639, 1978, 4088, 7005, 3256, 86, 2338, 1905, 1647, 16369
  - text: >-
      company.relationship: founder, None, founder/chairman, Relation, relation,
      CEO, chairman, investor, founder and CEO, founder/CEO, owner, chairman of
      management committee, founder and chairman, Chairman and Chief Executive
      Officer, general director, executive chairman, Chairman/founder, founder,
      chairman, ceo, former chairman and CEO, relation and chairman
  - text: 'variety: Western, Eastern'
  - text: >-
      Data.Fat.Saturated Fat: 2.009, 1.164, 1.86, 2.154, 0.568, 0.117, 1.11,
      0.049, 0.66, 1.242, 1.899, 0.596, 2.667, 0.044, 2.554, 0.633, 4.591,
      1.214, 0.121, 5.486
  - text: >-
      Date.Full: 8/26/1990, 3/24/1991, 3/31/1991, 4/7/1991, 4/14/1991,
      4/21/1991, 4/28/1991, 5/5/1991, 5/12/1991, 5/19/1991, 5/26/1991, 6/2/1991,
      6/9/1991, 6/16/1991, 6/23/1991, 6/30/1991, 7/7/1991, 7/14/1991, 7/21/1991,
      7/28/1991
inference: true
model-index:
  - name: SetFit with sentence-transformers/paraphrase-MiniLM-L3-v2
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: Unknown
          type: unknown
          split: test
        metrics:
          - type: accuracy
            value: 0.7512388503468781
            name: Accuracy

SetFit with sentence-transformers/paraphrase-MiniLM-L3-v2

This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/paraphrase-MiniLM-L3-v2 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.

The model has been trained using an efficient few-shot learning technique that involves:

Fine-tuning a Sentence Transformer with contrastive learning.
Training a classification head with features from the fine-tuned Sentence Transformer.

Model Details

Model Description

Model Type: SetFit
Sentence Transformer body: sentence-transformers/paraphrase-MiniLM-L3-v2
Classification head: a LogisticRegression instance
Maximum Sequence Length: 128 tokens
Number of Classes: 39 classes

Model Sources

Repository: SetFit on GitHub
Paper: Efficient Few-Shot Learning Without Prompts
Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts

Model Labels

Label	Examples
Month Number	'Incident.Date.Month: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12' 'bibliography.publication.month: 6, 11, 3, 8, 1, 10, 7, 2, 4, 5, 9, 12' 'mp_month: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12'
Date	'end_date: 12/20/22, 12/19/22, 12/15/22, 12/14/22, 12/13/22, 12/12/22, 12/11/22, 12/7/22, 12/6/22, 12/5/22, 12/4/22, 12/2/22, 11/29/22, 11/22/22, 11/21/22, 11/20/22, 11/19/22, 11/17/22, 11/15/22, 11/14/22' 'STOP_FRISK_DATE: 1/16/2017, 2/8/2017, 2/20/2017, 2/21/2017, 2/17/2017, 2/25/2017, 3/3/2017, 3/16/2017, 3/31/2017, 4/2/2017, 4/4/2017, 3/24/2017, 4/6/2017, 4/18/2017, 5/6/2017, 5/10/2017, 5/17/2017, 5/7/2017, 5/24/2017, 6/8/2017' 'start_date: 10/31/20, 10/30/20, 10/29/20, 10/27/20, 10/23/20, 10/28/20, 10/26/20, 10/24/20, 10/8/20, 10/22/20, 10/19/20, 10/21/20, 10/11/20, 10/20/20, 10/16/20, 10/18/20, 10/15/20, 10/12/20, 10/13/20, 10/14/20'
Categorical	'STOP_LOCATION_PATROL_BORO_NAME: PBMS, (nul, 986, 5 AV, PBMN, PBBX, 238, 233, 1011, 237, PBBS, 991, 154, PBBN, PBQN, PBQS, 183, 1022, 1025, 220' 'Subregion: Western Europe, Italy, Greece, Turkey, Western Asia, Africa (northeastern) and Red Sea, Africa (eastern), Africa (central), Africa (western), Africa (northern), Middle East (western), Middle East (southern), Middle East (eastern), Indian Ocean (western), Indian Ocean (southern), New Zealand, Kermadec Islands, Tonga Islands, Samoan and Wallis Islands, Fiji Islands' 'Procedure.Heart Attack.Quality: Average, Unknown, Worse, Better'
Year	'Year: 1998, 1997, 1996, 1995, 1993, 1994' 'cycle: 2020' 'metadata.acquisition date: 2009, 1924, 2010, 1968, 1982, 1997, 2012, 1983, 1996, 1900, 1990, 1995, 1931, 1960, 1966, 1955, 1993, 1979, 2001, 2011'
Longitude	'Longitude: 2,77228900, 2,77461100, 2,77370600, 2,77423900, 2,77654400, 2,79937600, 2,78064700, 2,77697400, 2,78928200, 2,78032200, 2,77731200, 2,77121300, 2,77167600, 2,78236500, 2,76694300, 2,77139500, 2,76872200, 2,76741500, 2,77156700, 2,82065100' 'long: 40.65531753386127, 35.52146509142811, 41.04610174058556, 37.25718863973695, 37.73038191275334, 38.78755702518432, 36.31538469187874, 38.3542649521305, 40.33741738725765, 36.831052736369664, 37.39711396680899, 38.28297641253209, 40.25037415629944, 39.12501528359793, 40.179108531876246, 38.165405118101205, 40.28234452941448, 37.1590112746327, 40.08056518798263, 38.45329795732872' 'Longitude: 6.85, 2.97, 2.53, -4.02, 10.87, 11.93, 12.7, 14.139, 14.426, 13.897, 14.83, 15.213, 15.064, 14.933, 14.962, 14.999, 12.02, 14.399, 23.336, 24.439'
Floating Point Number	'ins_premium: 784.55, 1053.48, 899.47, 827.34, 878.41, 835.5, 1068.73, 1137.87, 1273.89, 1160.13, 913.15, 861.18, 641.96, 803.11, 710.46, 649.06, 780.45, 872.51, 1281.55, 661.88' 'Data.Vitamins.Vitamin B12: 0.05, 0.56, 0.54, 0.36, 0.61, 0.38, 0.55, 0.58, 0.22, 0.37, 0.46, 0.3, 0.07, 0.5, 0.35, 0.16, 0.24, 0.44, 0.29, 0.85' 'Average Wage Appx MOE: 103382.66673939777, 116573.18275172487, 108787.21048470394, 118363.44825256945, 100311.98088082067, 27560.471912039546, 27835.56534877041, 27020.999829170632, 100720.90656498625, 26279.88466481348, 26033.491463487928, 25918.56067562003, 25523.8518942556, 68486.51231657575, 98614.90773401306, 63965.94799270596, 59979.385203569575, 67171.5207463371, 84156.83712285856, 76854.95603440655'
Slug	'Slug Geography: united-states, iowa, michigan, minnesota, north-dakota, south-dakota, wisconsin, minneapolis-st-paul-bloomington-mn-wi' 'Slug Detailed Occupation: physicians, physicians-surgeons, lawyers-judges-magistrates-other-judicial-workers, medical-health-services-managers, chief-executives-legislators, veterinarians, social-community-service-managers, securities-commodities-financial-services-sales-agents, petroleum-mining-geological-engineers-including-mining-safety-engineers, economists, miscellaneous-social-scientists-including-survey-researchers-sociologists, natural-sciences-managers, geoscientists-and-hydrologists-except-geographers, detectives-criminal-investigators, judicial-law-clerks, other-psychologists, architectural-engineering-managers, education-administrators, astronomers-physicists, public-relations-and-fundraising-managers' 'Slug Geography: united-states, arizona, california, nevada, oregon, los-angeles-long-beach-anaheim-ca, riverside-san-bernardino-ontario-ca, san-diego-carlsbad-ca, san-francisco-oakland-hayward-ca'
U.S. State Abbreviation	'State: AK, AL, AR, AZ, CA, CO, CT, DC, DE, FL, GA, HI, IA, ID, IL, IN, KS, KY, LA, MA' 'abbrev: AL, AK, AZ, AR, CA, CO, CT, DE, DC, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME' 'Facility.State: AL, AK, AZ, AR, CA, CO, CT, DE, DC, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME'
Month Name	'Month: JAN, FEB, MAR, APR, MAY, JUN, JUL, AUG, SEP, OCT, NOV, DEC' 'MONTH2: January, February, March, April, May, June, July, August, September, October, November, December' 'MONTH2: January, February, March, April, May, June, July, August, September, October, November, December'
Day of Month	'bibliography.publication.day: 1, 17, 16, 20, 29, 10, 14, 11, 9, 18, 19, 22, 25, 15, 6, 28, 27, 2, 12, 21' 'Date.Day: 26, 24, 31, 7, 14, 21, 28, 5, 12, 19, 2, 9, 16, 23, 30, 4, 11, 18, 25, 1' 'bibliography.publication.day: 1, 17, 16, 20, 29, 10, 14, 11, 9, 18, 19, 22, 25, 15, 6, 28, 27, 2, 12, 21'
Currency Code	'cur_name: AFN, DZD, AOA, ARS, AMD, AZN, BDT, INR, BYR, XOF, BTN, BOB, BIF, KHR, XAF, CVE, CNY, COP, USD, CDF'
Last Name	'answer: Spanberger, Freitas, Eastman, Bacon, Schaeffer, Schupp, Wagner, Schulte, Balter, Katko, Williams, Hale, Spartz, Tucker, Elliott, Hill, Golden, Crafts, Newman, Fricilone' 'candidat: Bush, Perot, Clinton'
Timestamp	'Modification: 26/06/2022 13:31:22, 12/04/2018 15:31:20, 26/06/2022 13:30:09, 26/06/2022 13:30:02, 26/06/2022 13:30:31, 26/06/2022 11:27:12, 26/06/2022 13:30:39, 28/10/2018 00:10:20, 12/04/2018 15:31:19, 26/06/2022 11:26:39, 12/07/2022 09:46:24, 12/04/2018 15:31:18, 21/10/2022 13:07:41, 21/10/2022 13:07:50, 16/09/2020 10:36:33, 26/06/2022 15:36:44, 24/07/2022 09:14:31, 12/04/2018 15:31:17, 26/06/2022 15:36:38, 12/07/2022 09:45:04' 'created_at: 12/21/22 09:28, 12/21/22 12:52, 12/16/22 18:27, 12/16/22 21:10, 12/14/22 10:39, 12/14/22 08:22, 12/15/22 18:31, 12/14/22 14:13, 12/13/22 09:36, 12/14/22 08:23, 12/14/22 15:40, 12/15/22 09:40, 12/7/22 10:47, 12/7/22 08:17, 12/7/22 17:56, 12/15/22 09:50, 11/30/22 09:25, 11/23/22 08:46, 12/1/22 09:39, 12/5/22 08:29' 'created_at: 12/30/20 12:29, 11/2/20 21:26, 11/2/20 22:16, 11/2/20 21:32, 11/2/20 22:01, 11/2/20 22:18, 11/2/20 22:26, 11/2/20 23:31, 11/2/20 21:49, 10/31/20 17:22, 11/1/20 14:39, 11/2/20 08:22, 10/29/20 14:16, 10/31/20 08:36, 10/29/20 11:08, 10/29/20 09:00, 10/29/20 16:13, 10/29/20 16:14, 10/30/20 15:45, 10/28/20 09:24'
Day of Week	'DAY2: Monday, Wednesday, Tuesday, Friday, Saturday, Thursday, Sunday' 'DAY2: Monday, Wednesday, Tuesday, Friday, Saturday, Thursday, Sunday' 'day: Sun, Sat, Thur, Fri'
Integer	'RF: 91.0, 92.0, 88.0, nan, 87.0, 81.0, 84.0, 70.0, 85.0, 83.0, 55.0, 86.0, 66.0, 62.0, 69.0, 82.0, 76.0, 77.0, 79.0, 68.0' 'GK diving: 7.0, 6.0, 9.0, 27.0, 91.0, 15.0, 90.0, 11.0, 10.0, 5.0, 85.0, 13.0, 3.0, 89.0, 84.0, 14.0, 2.0, 88.0, 12.0, 4.0' 'Household Income by Race Moe: 128.0, 286.0, 270.0, 445.0, 390.0, 315.0, 496.0, 734.0, 791.0, 135.0, 266.0, 231.99999999999997, 409.0, 304.0, 326.0, 488.0, 723.0, 531.0, 140.0, 275.0'
Street Address	'STOP_LOCATION_FULL_ADDRESS: 180 GREENWICH STREET, WALL STREET && BROADWAY, 75 GREENE STREET, 429 WEST BROADWAY, WEST STREET && CHAMBERS STREET, CHAMBERS STREET && WEST BROADWAY, CORTLANDT STREET && CHURCH STREET, 111 FULTON STREET, 25 CLIFF STREET, SPRING STREET && AVENUE OF THE AMERICAS, 130 CEDAR STREET, 225 LIBERTY STREET, BARCLAY STREET && WEST STREET, 153 GREENWICH STREET, BATTERY PLACE && STATE STREET, MERCER STREET && BROOME STREET, WEST STREET && CANAL STREET, BROADWAY && PRINCE STREET, WEST BROADWAY && AVENUE OF THE AMERICAS, 3 SOUTH STREET' 'STOP_LOCATION_FULL_ADDRESS: 180 GREENWICH STREET, WALL STREET && BROADWAY, 75 GREENE STREET, 429 WEST BROADWAY, WEST STREET && CHAMBERS STREET, CHAMBERS STREET && WEST BROADWAY, CORTLANDT STREET && CHURCH STREET, 111 FULTON STREET, 25 CLIFF STREET, SPRING STREET && AVENUE OF THE AMERICAS, 130 CEDAR STREET, 225 LIBERTY STREET, BARCLAY STREET && WEST STREET, 153 GREENWICH STREET, BATTERY PLACE && STATE STREET, MERCER STREET && BROOME STREET, WEST STREET && CANAL STREET, BROADWAY && PRINCE STREET, WEST BROADWAY && AVENUE OF THE AMERICAS, 3 SOUTH STREET' 'STOP_LOCATION_FULL_ADDRESS: 180 GREENWICH STREET, WALL STREET && BROADWAY, 75 GREENE STREET, 429 WEST BROADWAY, WEST STREET && CHAMBERS STREET, CHAMBERS STREET && WEST BROADWAY, CORTLANDT STREET && CHURCH STREET, 111 FULTON STREET, 25 CLIFF STREET, SPRING STREET && AVENUE OF THE AMERICAS, 130 CEDAR STREET, 225 LIBERTY STREET, BARCLAY STREET && WEST STREET, 153 GREENWICH STREET, BATTERY PLACE && STATE STREET, MERCER STREET && BROOME STREET, WEST STREET && CANAL STREET, BROADWAY && PRINCE STREET, WEST BROADWAY && AVENUE OF THE AMERICAS, 3 SOUTH STREET'
URL	'Flag: https://cdn.sofifa.org/flags/38.png, https://cdn.sofifa.org/flags/52.png, https://cdn.sofifa.org/flags/54.png, https://cdn.sofifa.org/flags/60.png, https://cdn.sofifa.org/flags/21.png, https://cdn.sofifa.org/flags/37.png, https://cdn.sofifa.org/flags/45.png, https://cdn.sofifa.org/flags/7.png, https://cdn.sofifa.org/flags/55.png, https://cdn.sofifa.org/flags/10.png, https://cdn.sofifa.org/flags/50.png, https://cdn.sofifa.org/flags/27.png, https://cdn.sofifa.org/flags/44.png, https://cdn.sofifa.org/flags/18.png, https://cdn.sofifa.org/flags/115.png, https://cdn.sofifa.org/flags/46.png, https://cdn.sofifa.org/flags/34.png, https://cdn.sofifa.org/flags/13.png, https://cdn.sofifa.org/flags/43.png, https://cdn.sofifa.org/flags/14.png' 'Club Logo: https://cdn.sofifa.org/24/18/teams/243.png, https://cdn.sofifa.org/24/18/teams/241.png, https://cdn.sofifa.org/24/18/teams/73.png, https://cdn.sofifa.org/24/18/teams/21.png, https://cdn.sofifa.org/24/18/teams/11.png, https://cdn.sofifa.org/24/18/teams/5.png, https://cdn.sofifa.org/24/18/teams/45.png, https://cdn.sofifa.org/24/18/teams/10.png, https://cdn.sofifa.org/24/18/teams/1.png, https://cdn.sofifa.org/24/18/teams/240.png, https://cdn.sofifa.org/24/18/teams/22.png, https://cdn.sofifa.org/24/18/teams/47.png, https://cdn.sofifa.org/24/18/teams/18.png, https://cdn.sofifa.org/24/18/teams/48.png, https://cdn.sofifa.org/24/18/teams/44.png, https://cdn.sofifa.org/24/18/teams/9.png, https://cdn.sofifa.org/24/18/teams/52.png, https://cdn.sofifa.org/24/18/teams/327.png, https://cdn.sofifa.org/24/18/teams/69.png, https://cdn.sofifa.org/24/18/teams/32.png' 'url: https://github.com/optimus-forecasting-and-polling/0ptimus-SC-VA7-November-2020/blob/main/virginia_cd_7_poll_toplines_tl_31_october_2020.pdf, https://projects.fivethirtyeight.com/polls/20201102_NE_UNLV.pdf, https://docs.google.com/spreadsheets/d/157HttGCHSc-6qx_hAWLg_KCrggbAUCbatOXH3WipShI/edit#gid=0, https://docs.google.com/spreadsheets/d/1RQaEpV6kT3qV2b5P2B_AQgnS2CAJdgJaioH_10hO4qU/edit#gid=1652054673, https://docs.google.com/spreadsheets/d/1sSzvXk5e3hpqSJiYtKN95Bm3VInlB_XtlWV8JQ57780/edit#gid=0, https://docs.google.com/spreadsheets/d/1iWSrZDo1yUpPUkqXffKUsO4w-lGKqhxb5aQGG-fU1Dw/edit#gid=1692435149, https://docs.google.com/spreadsheets/d/19LDCjGkae7_DJHp2KMN79Uq0aukFrQRibJLDjriTMqY/edit#gid=1236548106, https://docs.google.com/spreadsheets/d/1eBWQtr-cx1ECGu-dsFcF_VdhnFfyRPd3qz3zcTmhdFY/edit#gid=1166077921, https://projects.fivethirtyeight.com/polls/20201104_IL3_Victory.pdf, https://projects.fivethirtyeight.com/polls/20201104_IL6_Victory.pdf, https://projects.fivethirtyeight.com/polls/20201104_IL17_Victory.pdf, https://docs.google.com/spreadsheets/d/1C_aw1txi2S5CeUze-vC6TR28M5k0n0RcBGGRUlQEpDQ/edit#gid=2044611796, https://docs.google.com/spreadsheets/d/1RLsioeQZMNIHBeH1xo3nCGherCVpenMxoUxXGKaHUqw/edit#gid=1882933718, https://emersonpolling.reportablenews.com/pr/super-poll-sunday-pregame-polls-show-midwest-shift-for-biden-in-wisconsin-nebraska-s-2nd-district-and-vigo-county-indiana, https://outlook.office.com/mail/inbox/id/AAQkADg2MDVmMmNjLTRhYmUtNDA2NC04NzUzLWZlNWIxZGRkYmM3NQAQAO1Uc%2BZbJvFIsCShNRkrNvQ%3D, https://www.telemundopr.com/noticias/puerto-rico/https-www-telemundopr-com-noticias-puerto-rico-voto-2020-la-encuesta-final-elecciones-2020-puerto-rico-2143435-2/2143435/, https://314action.org/wp-content/uploads/2020/10/NCCD9Results1-1.pdf, https://www.abqjournal.com/1512949/extremely-close-race-for-2nd-congressional-district-ex-pollster-notes-race-between-torres-small-and-herrell-comes-down-to-turnout.html, http://stpetepolls.org/files/StPetePolls_2020_CD13GEN_October28_EH39F.pdf, https://www.scribd.com/document/482078454/Alaska-October-28-2020#from_embed'
U.S. State	'Geography: Arizona, California, Nevada, Oregon' 'State: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, District of Columbia, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine' 'Slug Geography: california'
Zip Code	'recipient_zip: 995084442, 99503, 995163436, 352124572, 35216, 35976, 358021277, 352174710, 35203, 35233, 35805, 72716, 72201, 72035, 72015, 72223, 72019, 72113, 72758, 72227' 'STOP_LOCATION_ZIP_CODE: (null), 20292, AVENUE, 5 AVEN, 10019, 22768, 10035, 10026, 10128, 24231, 10030, 10039, 23874, 11213, 11233, 100652, 10451, 23543, 100745, PROSPE' 'zip_codes: nan, 12081.0, 10090.0, 12423.0, 12420.0'
Country Name	'Nationality: Portugal, Argentina, Brazil, Uruguay, Germany, Poland, Spain, Belgium, Chile, Croatia, Wales, Italy, Slovenia, France, Gabon, Sweden, Netherlands, Denmark, Slovakia, England' 'adm0_name: Afghanistan, Algeria, Angola, Argentina, Armenia, Azerbaijan, Bangladesh, Bassas da India, Belarus, Benin, Bhutan, Bolivia, Burkina Faso, Burundi, Cambodia, Cameroon, Cape Verde, Central African Republic, Chad, China' 'Geography: United States'
Boolean	'ranked_choice_reallocated: False, True' 'wealth.how.was founder: True' 'internal: False'
Short text	'agestr: Under 5, 5 to 9, 10 to 14, 15 to 19, 20 to 24, 25 to 29, 30 to 34, 35 to 39, 40 to 44, 45 to 49, 50 to 54, 55 to 59, 60 to 64, 65 to 69, 70 to 74, 75 to 79, 80 to 84' "Show.Name: Tru, Miss Saigon, A Streetcar Named Desire 92, The Sisters Rosensweig, Beauty And The Beast, A Little More Magic, Broken Glass, Show Boat, Sunset Boulevard, The Shadow Box, Uncle Vanya, Smokey Joe'S Cafe, Having Our Say, Hamlet 95, The Rose Tattoo, A Month In The Country, Arcadia, Cats, Chronicle Of A Death Foretold, How To Succeed In Business Without Really Trying" 'Club: Real Madrid CF, FC Barcelona, Paris Saint-Germain, FC Bayern Munich, Manchester United, Chelsea, Juventus, Manchester City, Arsenal, Atlético Madrid, Borussia Dortmund, Milan, Tottenham Hotspur, Napoli, Inter, Liverpool, Roma, Beşiktaş JK, AS Monaco, Bayer 04 Leverkusen'
Occupation	'Detailed Occupation: Other managers, Cashiers, Retail salespersons, Driver/sales workers & truck drivers, Registered nurses' 'Detailed Occupation: Physicians, Physicians & surgeons, Lawyers, & judges, magistrates, & other judicial workers, Medical & health services managers, Chief executives & legislators, Veterinarians, Social & community service managers, Securities, commodities, & financial services sales agents, Petroleum, mining & geological engineers, including mining safety engineers, Economists, Miscellaneous social scientists, including survey researchers & sociologists, Natural sciences managers, Geoscientists and hydrologists, except geographers, Detectives & criminal investigators, Judicial law clerks, Other psychologists, Architectural & engineering managers, Education administrators, Astronomers & physicists, Public relations and fundraising managers' 'occupation: Operatives, Craftsmen, Sales, Other, Managers/admin, Professional/technical, Clerical/unskilled, Laborers, Transport, Service, nan, Household workers, Farm laborers, Farmers'
Partial timestamp	'Last Known Eruption: 8300 BCE, 4040 BCE, Unknown, 3600 BCE, 1282 CE, 104 BCE, 1538 CE, 1944 CE, 1302 CE, 8040 BCE, 2019 CE, 1230 CE, 1890 CE, 1867 CE, 1891 CE, 1050 BCE, 258 BCE, 140 CE, 1950 CE, 1888 CE' 'bibliography.publication.full: June, 1998, November, 1999, March, 1994, June 17, 2008, August 16, 2005, August 20, 2006, August 29, 2006, January 10, 2006, March, 2001, June, 2001, October 14, 1892, July, 1998, July, 2003, January, 1994, October 1997, August 16, 2013, February 11, 2006, June 9, 2008, January 1, 1870, April, 2001' 'Rating.Experience: Below, Same, None, Above'
Street Name	'STOP_LOCATION_STREET_NAME: GREENWICH STREET, WALL STREET, GREENE STREET, WEST BROADWAY, WEST STREET, CHAMBERS STREET, CORTLANDT STREET, FULTON STREET, CLIFF STREET, SPRING STREET, CEDAR STREET, LIBERTY STREET, BARCLAY STREET, BATTERY PLACE, MERCER STREET, BROADWAY, SOUTH STREET, THOMPSON STREET, JAY STREET, CHURCH STREET' 'STOP_LOCATION_STREET_NAME: GREENWICH STREET, WALL STREET, GREENE STREET, WEST BROADWAY, WEST STREET, CHAMBERS STREET, CORTLANDT STREET, FULTON STREET, CLIFF STREET, SPRING STREET, CEDAR STREET, LIBERTY STREET, BARCLAY STREET, BATTERY PLACE, MERCER STREET, BROADWAY, SOUTH STREET, THOMPSON STREET, JAY STREET, CHURCH STREET' 'STOP_LOCATION_STREET_NAME: GREENWICH STREET, WALL STREET, GREENE STREET, WEST BROADWAY, WEST STREET, CHAMBERS STREET, CORTLANDT STREET, FULTON STREET, CLIFF STREET, SPRING STREET, CEDAR STREET, LIBERTY STREET, BARCLAY STREET, BATTERY PLACE, MERCER STREET, BROADWAY, SOUTH STREET, THOMPSON STREET, JAY STREET, CHURCH STREET'
Full Name	"cand_nm: Rubio, Marco, Santorum, Richard J., Perry, James R. (Rick), Carson, Benjamin S., Cruz, Rafael Edward 'Ted', Paul, Rand, Clinton, Hillary Rodham, Sanders, Bernard, Fiorina, Carly, Huckabee, Mike, Pataki, George E., O'Malley, Martin Joseph, Graham, Lindsey O., Bush, Jeb, Trump, Donald J., Jindal, Bobby, Christie, Christopher J., Walker, Scott, Stein, Jill, Webb, James Henry Jr." 'sponsor_candidate: None, Vern Buchanan, Joyce Ann Elliott, Xochitl Torres Small, Desiree Tims, Morris Durham Davis, John Katko, Stephen Daniel, Nancy Mace, Alaina Shearer, Wesley Hunt, Scott Perry, J.D. Scholten, Jim Bognet, Angie Craig, Brynne S. Kennedy, Young Kim, Ammar Campa-Najjar, Donna E. Shalala, Jennifer T. Wexton' 'bibliography.author.name: Austen, Jane, Gilman, Charlotte Perkins, Carroll, Lewis, Shelley, Mary Wollstonecraft, Kafka, Franz, Twain, Mark, Wilde, Oscar, Douglass, Frederick, Ibsen, Henrik, Melville, Herman, Doyle, Arthur Conan, Dickens, Charles, Joyce, James, Swift, Jonathan, Stoker, Bram, Machiavelli, Niccolo, Tolstoy, Leo, graf, Grimm, Wilhelm, Vatsyayana, Unknown'
Very short text	'above_ground_sighter_measurement: None, FALSE, 4, 3, 30, 10, 6, 24, 8, 25, 5, 50, 70, 12, 2, 20, 7, 13, 15, 28' 'status: N, Y, REMOVE, None, 1, ?, H, R, M, T' 'review_reason_code: 2, 1, 4, None, 5, 3, 7, 3?, 8, D, ?, 3, 1, 1 or 2, D or 1, 7B, 1, 2, 1 OR 2, D OR 2, B, 4?'
URI	'url: https://docs.cdn.yougov.com/c5o6xiw8t9/econtoplines.pdf, https://docs.cdn.yougov.com/by8wjw1hur/econTabReport.pdf, https://subscriber.politicopro.com/newsletter/2022/12/who-supports-the-payment-pause-00072673, https://news.yahoo.com/new-poll-shows-stark-partisan-divide-when-it-comes-to-americans-view-of-schools-132510314.html, https://harvardharrispoll.com/wp-content/uploads/2022/12/HHP_Dec2022_KeyResults.pdf, https://echeloninsights.com/in-the-news/december-2022-omnibus-2/, https://docs.cdn.yougov.com/b94ttrxy3v/econtoplines.pdf, https://docs.cdn.yougov.com/urts2xadfd/econTabReport.pdf, https://www.foxnews.com/politics/fox-news-poll-americans-show-little-enthusiasm-biden-trump-rematch-2024, https://poll.qu.edu/poll-release?releaseid=3863, https://www.usatoday.com/story/news/politics/2022/12/13/trump-support-gop-2024-presidential-race-poll/10882346002/, https://www.wsj.com/articles/ron-desantis-holds-early-lead-over-donald-trump-among-gop-primary-voters-wsj-poll-shows-11670989311?mod=hp_lead_pos5, https://www.cnn.com/2022/12/14/politics/biden-trump-2024-poll/index.html, https://docs.cdn.yougov.com/dshfq4wqyr/econtoplines.pdf, https://docs.cdn.yougov.com/qsanp37uhh/econTabReport.pdf, https://www.yahoo.com/news/poll-trump-loses-ground-with-republicans-after-kanye-west-nick-fuentes-dinner-100204385.html, https://docs.cdn.yougov.com/regijt79ge/November_Georgia_Ads_joined_earlier.pdf, https://docs.cdn.yougov.com/xcvx6iu6em/November_Georgia_Ads_joined.pdf, https://news.gallup.com/poll/406892/party-images-stable-midterm-elections.aspx, https://docs.cdn.yougov.com/2zebcvjoec/econtoplines.pdf'
Latitude	'Latitude: 48,87217700, 48,85543800, 48,87416100, 48,87322500, 48,87422500, 48,84189000, 48,86617200, 48,87112100, 48,86552200, 48,87623100, 48,85609000, 48,85642700, 48,86853300, 48,87465400, 48,86995000, 48,85654000, 48,87022000, 48,86962600, 48,85663200, 48,83476200' 'Latitude: 50.17, 45.775, 42.17, 38.87, 43.25, 42.6, 41.73, 40.827, 40.821, 40.73, 39.48, 38.789, 38.638, 38.49, 38.404, 37.748, 37.1, 36.77, 39.284, 37.615' 'lat: 40.7940823884086, 40.7948509408039, 40.7667178072558, 40.7697032606755, 40.797533370163, 40.7902561000937, 40.7693045133578, 40.7942883045566, 40.7729752391435, 40.7903128889029, 40.7762126854894, 40.7725908847499, 40.7931811701082, 40.7917367820255, 40.7829723919744, 40.7742879599026, 40.7823507678183, 40.7919669739962, 40.7702795904962, 40.7698124821507'
Time	'STOP_FRISK_TIME: 14:26:00, 11:10:00, 11:35:00, 13:20:00, 21:25:00, 20:00:00, 19:58:00, 13:15:00, 8:16:00, 18:44:00, 22:30:00, 4:45:00, 18:30:00, 0:00:00, 9:58:00, 11:15:00, 13:00:00, 8:00:00, 14:57:00, 4:15:00' 'STOP_FRISK_TIME: 14:26:00, 11:10:00, 11:35:00, 13:20:00, 21:25:00, 20:00:00, 19:58:00, 13:15:00, 8:16:00, 18:44:00, 22:30:00, 4:45:00, 18:30:00, 0:00:00, 9:58:00, 11:15:00, 13:00:00, 8:00:00, 14:57:00, 4:15:00' 'STOP_FRISK_TIME: 14:26:00, 11:10:00, 11:35:00, 13:20:00, 21:25:00, 20:00:00, 19:58:00, 13:15:00, 8:16:00, 18:44:00, 22:30:00, 4:45:00, 18:30:00, 0:00:00, 9:58:00, 11:15:00, 13:00:00, 8:00:00, 14:57:00, 4:15:00'
Postal Code	'Code postal: 77700.0, nan'
Country ISO Code	'Runner-up Nationality: AUS, GBR, NZL, FRA, USA, RSA, CZE, ARG, GER, SUI, ESP, CRO, ROM, DEN, TCH, URS, CZ, SRB, CND, SWE' 'Champion Nationality: AUS, FRA, GBR, NZL, USA, SRB, SUI, SWE, CZE, ESP, GER, NED, CRO, BRA, RUS'
First Name	'Top Name: Mary, Linda, Debra, Lisa, Michelle, Jennifer, Jessica, Samantha, Ashley, Hannah, Emily, Madison, Emma, Isabella, Sophia, Olivia, John, Robert, James, David'
City Name	'Incident.Location.City: Shelton, Aloha, Wichita, San Francisco, Evans, Guthrie, Chandler, Assaria, Burlington, Knoxville, Stockton, Freeport, Columbus, Des Moines, New Orleans, Huntley, Salt Lake City, Strong, Syracuse, England'
Color	'color: Yellow, Black, White' 'highlight_fur_color: None, Cinnamon, White, Gray, Cinnamon, White, Gray, White, Black, Cinnamon, White, Black, Black, White, Black, Cinnamon, Gray, Black' 'primary_fur_color: None, Gray, Cinnamon, Black'
License Plate	'plate: AZIZ714, BATBOX1, BBOMBS, BEACHY1, BLK PWR5, BOT TAK, CHERIPI, CIO FTW, DAVES88, DMOBGFY, DOITFKR, EGGPUTT, F DIABDZ, FJ 666, FKK OFF, FKN BLAK, FLT ATCK, F LUPUS, HVNNHEL, H8DES'
AM/PM	'shift: PM, AM'
Company Name	"company.name: Microsoft, Berkshire Hathaway, Telmex, F. Hoffmann-La Roche, Zara, Henderson Land Development, Oracle, Lin Yuan Group, Aldi, Sun Hung Kai Properties, Kingdom Holding Company, Koch industries, Cheung king, Walmart, Seibu Corporation, Las Vegas Sands, Aldi Nord, Tetra Pak, BMW, L'Oreal"
Secondary Address	'STOP_LOCATION_APARTMENT: (null), 2, 7, 4TH, 2FL, ROOF, ROOF T, BASEME, LOBBY, 17TH, 2 FLOO, 12, 1701, HALLWA, 1E, 5D, SIDEWA, FRONT, 12C, None'

Evaluation

Metrics

Label	Accuracy
all	0.7512

Uses

Direct Use for Inference

First install the SetFit library:

pip install setfit

Then you can load this model and run inference.

from setfit import SetFitModel

# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("quantisan/paraphrase-MiniLM-L3-v2-93dataset")
# Run inference
preds = model("variety: Western, Eastern")

Training Details

Training Set Metrics

Training set	Min	Median	Max
Word count	2	22.3314	85

Label	Training Sample Count
Categorical	8
Timestamp	5
Date	8
Integer	8
Partial timestamp	4
Short text	8
Very short text	3
AM/PM	1
Boolean	8
City Name	1
Color	3
Company Name	1
Country ISO Code	2
Country Name	8
Currency Code	1
Day of Month	4
Day of Week	4
First Name	1
Floating Point Number	8
Full Name	8
Last Name	2
Latitude	4
License Plate	1
Longitude	4
Month Name	6
Month Number	4
Occupation	3
Postal Code	1
Secondary Address	1
Slug	8
Street Address	3
Street Name	3
Time	3
U.S. State	8
U.S. State Abbreviation	6
URI	1
URL	8
Year	8
Zip Code	4

Training Hyperparameters

batch_size: (8, 8)
num_epochs: (4, 4)
max_steps: -1
sampling_strategy: oversampling
body_learning_rate: (2e-05, 1e-05)
head_learning_rate: 0.01
loss: CosineSimilarityLoss
distance_metric: cosine_distance
margin: 0.25
end_to_end: False
use_amp: False
warmup_proportion: 0.1
l2_weight: 0.01
seed: 42
eval_max_steps: -1
load_best_model_at_end: True

Training Results

Epoch	Step	Training Loss	Validation Loss
0.0003	1	0.3882	-
0.0140	50	0.1864	-
0.0280	100	0.1588	-
0.0421	150	0.15	-
0.0561	200	0.1537	-
0.0701	250	0.1325	-
0.0841	300	0.132	-
0.0981	350	0.1149	-
0.1121	400	0.1198	-
0.1262	450	0.1035	-
0.1402	500	0.0907	-
0.1542	550	0.0917	-
0.1682	600	0.0875	-
0.1822	650	0.0803	-
0.1962	700	0.0669	-
0.2103	750	0.0671	-
0.2243	800	0.0614	-
0.2383	850	0.0642	-
0.2523	900	0.0481	-
0.2663	950	0.0548	-
0.2803	1000	0.0346	-
0.2944	1050	0.0406	-
0.3084	1100	0.0403	-
0.3224	1150	0.0349	-
0.3364	1200	0.0312	-
0.3504	1250	0.0378	-
0.3645	1300	0.0335	-
0.3785	1350	0.0323	-
0.3925	1400	0.0234	-
0.4065	1450	0.0313	-
0.4205	1500	0.022	-
0.4345	1550	0.0326	-
0.4486	1600	0.0233	-
0.4626	1650	0.0195	-
0.4766	1700	0.0254	-
0.4906	1750	0.0211	-
0.5046	1800	0.0198	-
0.5186	1850	0.0201	-
0.5327	1900	0.0216	-
0.5467	1950	0.0174	-
0.5607	2000	0.0176	-
0.5747	2050	0.0234	-
0.5887	2100	0.0172	-
0.6027	2150	0.0129	-
0.6168	2200	0.0151	-
0.6308	2250	0.015	-
0.6448	2300	0.0164	-
0.6588	2350	0.0137	-
0.6728	2400	0.014	-
0.6869	2450	0.0154	-
0.7009	2500	0.0135	-
0.7149	2550	0.0164	-
0.7289	2600	0.0139	-
0.7429	2650	0.0164	-
0.7569	2700	0.0106	-
0.7710	2750	0.0084	-
0.7850	2800	0.0133	-
0.7990	2850	0.0114	-
0.8130	2900	0.0066	-
0.8270	2950	0.0091	-
0.8410	3000	0.0126	-
0.8551	3050	0.0107	-
0.8691	3100	0.0068	-
0.8831	3150	0.006	-
0.8971	3200	0.007	-
0.9111	3250	0.0155	-
0.9251	3300	0.0111	-
0.9392	3350	0.0049	-
0.9532	3400	0.0076	-
0.9672	3450	0.0092	-
0.9812	3500	0.0086	-
0.9952	3550	0.0061	-
1.0	3567	-	0.1341
1.0093	3600	0.0073	-
1.0233	3650	0.0065	-
1.0373	3700	0.0063	-
1.0513	3750	0.0094	-
1.0653	3800	0.0114	-
1.0793	3850	0.0084	-
1.0934	3900	0.0098	-
1.1074	3950	0.0058	-
1.1214	4000	0.0045	-
1.1354	4050	0.018	-
1.1494	4100	0.0077	-
1.1634	4150	0.0067	-
1.1775	4200	0.0061	-
1.1915	4250	0.0037	-
1.2055	4300	0.0045	-
1.2195	4350	0.0033	-
1.2335	4400	0.0067	-
1.2475	4450	0.0054	-
1.2616	4500	0.0057	-
1.2756	4550	0.004	-
1.2896	4600	0.0033	-
1.3036	4650	0.0076	-
1.3176	4700	0.0045	-
1.3317	4750	0.0068	-
1.3457	4800	0.0043	-
1.3597	4850	0.0049	-
1.3737	4900	0.0045	-
1.3877	4950	0.0055	-
1.4017	5000	0.0065	-
1.4158	5050	0.0029	-
1.4298	5100	0.0041	-
1.4438	5150	0.0064	-
1.4578	5200	0.0031	-
1.4718	5250	0.0078	-
1.4858	5300	0.0031	-
1.4999	5350	0.004	-
1.5139	5400	0.0035	-
1.5279	5450	0.0062	-
1.5419	5500	0.0062	-
1.5559	5550	0.0065	-
1.5699	5600	0.0036	-
1.5840	5650	0.0037	-
1.5980	5700	0.0047	-
1.6120	5750	0.0037	-
1.6260	5800	0.0028	-
1.6400	5850	0.0052	-
1.6541	5900	0.0043	-
1.6681	5950	0.0029	-
1.6821	6000	0.0064	-
1.6961	6050	0.0031	-
1.7101	6100	0.0023	-
1.7241	6150	0.002	-
1.7382	6200	0.0041	-
1.7522	6250	0.0033	-
1.7662	6300	0.0043	-
1.7802	6350	0.0023	-
1.7942	6400	0.0036	-
1.8082	6450	0.0024	-
1.8223	6500	0.0016	-
1.8363	6550	0.003	-
1.8503	6600	0.0043	-
1.8643	6650	0.0043	-
1.8783	6700	0.0017	-
1.8923	6750	0.0018	-
1.9064	6800	0.0029	-
1.9204	6850	0.0026	-
1.9344	6900	0.0039	-
1.9484	6950	0.0019	-
1.9624	7000	0.0041	-
1.9765	7050	0.0019	-
1.9905	7100	0.0023	-
2.0	7134	-	0.1286
2.0045	7150	0.0016	-
2.0185	7200	0.0017	-
2.0325	7250	0.0016	-
2.0465	7300	0.0019	-
2.0606	7350	0.0015	-
2.0746	7400	0.0016	-
2.0886	7450	0.0015	-
2.1026	7500	0.0015	-
2.1166	7550	0.0034	-
2.1306	7600	0.0043	-
2.1447	7650	0.0016	-
2.1587	7700	0.0016	-
2.1727	7750	0.0015	-
2.1867	7800	0.0015	-
2.2007	7850	0.0017	-
2.2147	7900	0.0013	-
2.2288	7950	0.0016	-
2.2428	8000	0.0013	-
2.2568	8050	0.0039	-
2.2708	8100	0.0053	-
2.2848	8150	0.0025	-
2.2989	8200	0.0015	-
2.3129	8250	0.0012	-
2.3269	8300	0.006	-
2.3409	8350	0.0014	-
2.3549	8400	0.0014	-
2.3689	8450	0.0028	-
2.3830	8500	0.0015	-
2.3970	8550	0.0019	-
2.4110	8600	0.0017	-
2.4250	8650	0.002	-
2.4390	8700	0.0016	-
2.4530	8750	0.0014	-
2.4671	8800	0.0021	-
2.4811	8850	0.0012	-
2.4951	8900	0.0015	-
2.5091	8950	0.0012	-
2.5231	9000	0.0012	-
2.5371	9050	0.0016	-
2.5512	9100	0.0016	-
2.5652	9150	0.0013	-
2.5792	9200	0.0028	-
2.5932	9250	0.0013	-
2.6072	9300	0.0011	-
2.6213	9350	0.0035	-
2.6353	9400	0.0013	-
2.6493	9450	0.0012	-
2.6633	9500	0.0037	-
2.6773	9550	0.0012	-
2.6913	9600	0.0011	-
2.7054	9650	0.0037	-
2.7194	9700	0.0012	-
2.7334	9750	0.0013	-
2.7474	9800	0.0013	-
2.7614	9850	0.001	-
2.7754	9900	0.0011	-
2.7895	9950	0.0012	-
2.8035	10000	0.0012	-
2.8175	10050	0.001	-
2.8315	10100	0.001	-
2.8455	10150	0.0011	-
2.8595	10200	0.0009	-
2.8736	10250	0.0018	-
2.8876	10300	0.0013	-
2.9016	10350	0.0009	-
2.9156	10400	0.0033	-
2.9296	10450	0.0034	-
2.9437	10500	0.0011	-
2.9577	10550	0.0013	-
2.9717	10600	0.0009	-
2.9857	10650	0.0009	-
2.9997	10700	0.0011	-
3.0	10701	-	0.1205
3.0137	10750	0.0009	-
3.0278	10800	0.0009	-
3.0418	10850	0.0032	-
3.0558	10900	0.0008	-
3.0698	10950	0.0013	-
3.0838	11000	0.0033	-
3.0978	11050	0.0011	-
3.1119	11100	0.0008	-
3.1259	11150	0.0009	-
3.1399	11200	0.0008	-
3.1539	11250	0.0033	-
3.1679	11300	0.0032	-
3.1819	11350	0.0008	-
3.1960	11400	0.0008	-
3.2100	11450	0.001	-
3.2240	11500	0.0009	-
3.2380	11550	0.0008	-
3.2520	11600	0.0008	-
3.2660	11650	0.0008	-
3.2801	11700	0.0009	-
3.2941	11750	0.0008	-
3.3081	11800	0.0007	-
3.3221	11850	0.0008	-
3.3361	11900	0.0008	-
3.3502	11950	0.0009	-
3.3642	12000	0.0008	-
3.3782	12050	0.0007	-
3.3922	12100	0.0009	-
3.4062	12150	0.0008	-
3.4202	12200	0.0008	-
3.4343	12250	0.0009	-
3.4483	12300	0.0008	-
3.4623	12350	0.0008	-
3.4763	12400	0.0008	-
3.4903	12450	0.0009	-
3.5043	12500	0.0007	-
3.5184	12550	0.0008	-
3.5324	12600	0.0009	-
3.5464	12650	0.0031	-
3.5604	12700	0.0009	-
3.5744	12750	0.0008	-
3.5884	12800	0.0007	-
3.6025	12850	0.0007	-
3.6165	12900	0.0007	-
3.6305	12950	0.0008	-
3.6445	13000	0.0007	-
3.6585	13050	0.0008	-
3.6726	13100	0.0007	-
3.6866	13150	0.0007	-
3.7006	13200	0.0008	-
3.7146	13250	0.0007	-
3.7286	13300	0.0031	-
3.7426	13350	0.0006	-
3.7567	13400	0.0008	-
3.7707	13450	0.0007	-
3.7847	13500	0.0006	-
3.7987	13550	0.0007	-
3.8127	13600	0.0008	-
3.8267	13650	0.0007	-
3.8408	13700	0.0008	-
3.8548	13750	0.0007	-
3.8688	13800	0.0007	-
3.8828	13850	0.0007	-
3.8968	13900	0.0007	-
3.9108	13950	0.0007	-
3.9249	14000	0.0031	-
3.9389	14050	0.003	-
3.9529	14100	0.0007	-
3.9669	14150	0.0007	-
3.9809	14200	0.0007	-
3.9950	14250	0.0007	-
4.0	14268	-	0.1155

Framework Versions

Python: 3.11.10
SetFit: 1.1.0
Sentence Transformers: 3.2.0
Transformers: 4.45.2
PyTorch: 2.4.1+cu124
Datasets: 3.0.1
Tokenizers: 0.20.1

Citation

BibTeX

@article{https://doi.org/10.48550/arxiv.2209.11055,
    doi = {10.48550/ARXIV.2209.11055},
    url = {https://arxiv.org/abs/2209.11055},
    author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
    keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
    title = {Efficient Few-Shot Learning Without Prompts},
    publisher = {arXiv},
    year = {2022},
    copyright = {Creative Commons Attribution 4.0 International}
}