Edit model card

SetFit with intfloat/e5-base-v2

This is a SetFit model that can be used for Text Classification. This SetFit model uses intfloat/e5-base-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:

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

Model Details

Model Description

Model Sources

Model Labels

Label Examples
Date
  • 'end_date: 11/3/20, 11/2/20, 11/1/20, 10/31/20, 10/30/20, 10/29/20, 10/28/20, 10/27/20, 10/26/20, 10/25/20, 10/24/20, 10/23/20, 10/22/20, 10/21/20, 10/20/20, 10/19/20, 10/18/20, 10/17/20, 10/16/20, 10/15/20'
  • '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'
ID
  • 'cur_id: 0.0'
  • 'pt_id: 15, 14, 17, 18'
Likert scale
  • 'Procedure.Pneumonia.Quality: Average, Worse, Unknown, Better'
  • 'Rating.Safety: Above, Below, Same, None'
  • 'Rating.Readmission: Below, Above, None, Same'
Structured field
  • 'metadata.formats.types: text/plain,text/plain; charset=us-ascii,application/pdf,application/x-mobipocket-ebook,application/zip,application/rdf+xml,application/epub+zip,text/html; charset=us-ascii, application/x-mobipocket-ebook,text/plain; charset=us-ascii,text/html; charset=us-ascii,application/zip,application/rdf+xml,application/epub+zip,text/plain, application/x-mobipocket-ebook,text/plain; charset=us-ascii,text/plain,text/html; charset=us-ascii,application/zip,application/rdf+xml,application/epub+zip,application/pdf, text/html; charset=iso-8859-1,text/plain,application/zip,application/rdf+xml,application/epub+zip,text/plain; charset=us-ascii,application/x-mobipocket-ebook, text/plain; charset=us-ascii,text/rtf,application/x-mobipocket-ebook,application/zip,application/rdf+xml,application/epub+zip,text/html; charset=iso-8859-1,text/plain, image/jpeg,text/html; charset=iso-8859-1,application/x-mobipocket-ebook,application/zip,text/plain; charset=iso-8859-1,application/epub+zip,application/rdf+xml,text/plain, text/html,text/plain; charset=us-ascii,application/x-mobipocket-ebook,application/zip,application/rdf+xml,application/epub+zip,text/plain, image/jpeg,text/html; charset=iso-8859-1,text/plain,application/zip,text/plain; charset=iso-8859-1,application/epub+zip,application/rdf+xml,application/x-mobipocket-ebook, text/plain,text/plain; charset=us-ascii,text/html; charset=us-ascii,application/zip,application/rdf+xml,application/epub+zip,application/x-mobipocket-ebook, application/x-mobipocket-ebook,text/plain; charset=us-ascii,text/plain,application/zip,application/rdf+xml,application/epub+zip,text/html; charset=us-ascii, text/html; charset=us-ascii,text/plain; charset=us-ascii,application/x-mobipocket-ebook,application/zip,application/rdf+xml,application/epub+zip,text/plain, application/rdf+xml,text/html; charset=iso-8859-1,application/x-mobipocket-ebook,application/zip,text/plain; charset=iso-8859-1,application/epub+zip,text/plain; charset=us-ascii,text/plain, text/plain; charset=us-ascii,application/x-mobipocket-ebook,text/html; charset=iso-8859-1,application/zip,text/plain; charset=iso-8859-1,application/epub+zip,application/rdf+xml,text/plain, text/html; charset=iso-8859-1,text/plain; charset=us-ascii,text/plain,application/rdf+xml,application/epub+zip,text/plain; charset=iso-8859-1,application/x-mobipocket-ebook, application/rdf+xml,text/html; charset=iso-8859-1,text/plain,application/zip,text/plain; charset=iso-8859-1,application/epub+zip,text/plain; charset=us-ascii,application/x-mobipocket-ebook, text/plain,text/plain; charset=us-ascii,application/x-mobipocket-ebook,application/rdf+xml,application/epub+zip,text/html; charset=us-ascii, image/jpeg,text/html; charset=utf-8,text/plain; charset=us-ascii,application/x-mobipocket-ebook,application/zip,application/rdf+xml,application/epub+zip,text/plain; charset=iso-8859-1,text/plain, text/html; charset=iso-8859-1,application/x-mobipocket-ebook,application/zip,application/rdf+xml,application/epub+zip,text/plain; charset=us-ascii,text/plain, text/plain,text/plain; charset=us-ascii,application/x-mobipocket-ebook,text/plain; charset=iso-8859-1,application/epub+zip,application/rdf+xml,text/html; charset=us-ascii, application/x-mobipocket-ebook,text/plain; charset=us-ascii,application/pdf,text/html; charset=us-ascii,application/zip,application/rdf+xml,application/epub+zip,text/plain'
  • 'Orange Bowl: Georgia 34, Michigan 11, Texas A&M 41, North Carolina 27, Florida 36, Virginia 28, Alabama 45, Oklahoma 34, Wisconsin 34, Miami 24, Florida State 33, Michigan 32, Clemson 37, Oklahoma 17, Georgia Tech 49, Mississippi State 34, Clemson 40, Ohio State 35, Florida State 31, Northern Illinois 10, West Virginia 70, Clemson 33, Stanford 40, Virginia Tech 12, Iowa 24, Georgia Tech 14, Virginia Tech 20, Cincinnati 7, Kansas 24, Virginia Tech 21, Louisville 24, Wake Forest 13, Penn State 26, Florida State 23, USC 55, Oklahoma 19, Miami (FL) 16, Florida State 14, USC 38, Iowa 17'
  • 'combination_of_primary_and_highlight_color: +, Gray+Cinnamon, Cinnamon+, Gray+, Cinnamon+White, Gray+White, Cinnamon+Gray, Gray+Cinnamon, White, Cinnamon+Gray, White, Gray+Black, Cinnamon, White, Black+, Gray+Black, Black+White, Black+Cinnamon, Gray+Black, White, Cinnamon+Black, Black+Gray, Gray+Black, Cinnamon, Black+Cinnamon, White, Cinnamon+Black, White'
Alphanumeric identifier
  • 'ID Geography: 16000US1714000'
  • 'ID Geography: 04000US06'
  • 'ID Geography: 01000US, 04000US51'
Longitude
  • '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'
  • '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'
Gender
  • 'SUSPECT_SEX: MALE, FEMALE, (null), 19, 39, 23, 24'
  • 'sex: Female, Male'
  • 'Person.Gender: Male, Female, Unknown'
Very short text
  • 'status: N, Y, REMOVE, None, 1, ?, H, R, M, T'
  • 'above_ground_sighter_measurement: None, FALSE, 4, 3, 30, 10, 6, 24, 8, 25, 5, 50, 70, 12, 2, 20, 7, 13, 15, 28'
  • '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?'
Color
  • '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'
  • 'color: Yellow, Black, White'
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'
Region
  • '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'
  • 'Region: Mediterranean and Western Asia, Africa and Red Sea, Middle East and Indian Ocean, New Zealand to Fiji, Melanesia and Australia, Indonesia, Philippines and SE Asia, Japan, Taiwan, Marianas, Kuril Islands, Kamchatka and Mainland Asia, Alaska, Canada and Western USA, Hawaii and Pacific Ocean, México and Central America, South America, West Indies, Iceland and Arctic Ocean, Atlantic Ocean, Antarctica'
  • 'origin: usa, japan, europe'
Slug
  • 'Slug Geography: united-states'
  • 'Slug University: doctoral-universities, associates-colleges-high-transfer-high-traditional, doctoral-universities-highest-research-activity, doctoral-universities-higher-research-activity, doctoral-universities-moderate-research-activity, masters-colleges-universities-larger-programs, not-applicable-not-in-carnegie-universe-not-accredited-or-nondegree-granting'
  • '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'
Numeric
  • 'cat_indent: 0'
  • 'et_idx: 0, 6, 5, 2, 3, 4, 1, 8, 7'
  • 'metadata.downloads: 36576, 26363, 18882, 17128, 15683, 15347, 13638, 13237, 12794, 11625, 11270, 11125, 11068, 10568, 10312, 10014, 9852, 9690, 9681, 9580'
Timestamp
  • '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'
  • '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: 12/21/22 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'
Country ISO Code
  • "Runner-up Nationality (Men's): None, USA, BRA, AUS, RSA, FRA, CND, RUS, GBR, BEL, GER, ESP, NED, POL, ARG, CZE, YUG, TCH, URS"
  • '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'
Latitude
  • '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: 83.92115933668057, 89.53277415300325, 85.37696959908148, 85.44622332365381, 84.28538158324413, 87.96664079539569, 86.11414393337242, 85.43864590316868, 87.65474214915454, 81.67725407101064, 90.47817498708324, 89.87993043195812, 81.56791356025577, 88.48808747114165, 89.3843538611984, 87.5218603199103, 83.99238693700401, 82.50195719071465, 85.84865551792468, 87.92121711225418'
  • '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'
Letter grade
  • 'fte_grade: B+, B, B/C, A, A-, None, C, A/B, B-, A+, C/D'
  • 'fte_grade: A/B, None, A-, B+, B, B-, C, B/C, A+, A, C-, C+, C/D, F'
  • 'fte_grade: B/C, B-, A-, A, B+, B, C/D, A/B, A+, C+, None, F'
U.S. State Abbreviation
  • 'state2: AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD'
  • 'recipient_st: AK, AL, AR, AZ, CA, CO, CT, DC, FL, GA, HI, IA, ID, IL, IN, KA, KS, KY, LA, MA'
  • 'State: AK, AL, AR, AZ, CA, CO, CT, DC, DE, FL, GA, HI, IA, ID, IL, IN, KS, KY, LA, MA'
URI
Floating Point Number
  • 'age: 228.0, 248.0, 236.0, 213.0, 263.0, 253.0, 225.0, 233.0, 239.0, 244.0, 224.0, 221.0, 257.0, 210.0, 237.0, 247.0, 256.0, 269.0, 259.0, 227.0'
  • 'sulphates: 0.56, 0.68, 0.65, 0.58, 0.46, 0.47, 0.57, 0.8, 0.54, 0.52, 1.56, 0.88, 0.93, 0.75, 1.28, 0.5, 1.08, 0.53, 0.91, 0.63'
  • 'total sulfur dioxide: 34.0, 67.0, 54.0, 60.0, 40.0, 59.0, 21.0, 18.0, 102.0, 65.0, 29.0, 145.0, 148.0, 103.0, 56.0, 71.0, 37.0, 23.0, 11.0, 35.0'
Race/Ethnicity
  • 'SUSPECT_RACE_DESCRIPTION: (null), WHITE, BLACK HISPANIC, BLACK, WHITE HISPANIC, ASIAN/PAC.ISL, AMER IND, MALE'
  • 'race: black, white, other'
  • 'Person.Race: Asian, White, Hispanic, African American, Other, Unknown, Native American'
Occupation
  • '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'
  • 'Detailed Occupation: Other managers, Cashiers, Retail salespersons, Driver/sales workers & truck drivers, Registered nurses'
  • 'occupation: Operatives, Craftsmen, Sales, Other, Managers/admin, Professional/technical, Clerical/unskilled, Laborers, Transport, Service, nan, Household workers, Farm laborers, Farmers'
Country Name
  • 'County: Baldwin County, AL, Calhoun County, AL, Coffee County, AL, Colbert County, AL, Covington County, AL, Cullman County, AL, Dale County, AL, Dallas County, AL, Etowah County, AL, Jackson County, AL, Jefferson County, AL, Lee County, AL, Limestone County, AL, Madison County, AL, Marshall County, AL, Mobile County, AL, Montgomery County, AL, Perry County, AL, Pike County, AL, Randolph County, AL'
  • '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'
  • 'Nation: Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, The Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan'
U.S. State
  • 'Geography: Arizona, California, Nevada, Oregon'
  • 'state: None, Florida, Iowa, Pennsylvania, Nevada, Georgia, South Carolina, Nebraska CD-2, Montana, Maine, Maine CD-2, Maine CD-1, Arizona, North Carolina, Texas, Wyoming, West Virginia, Wisconsin, Washington, Vermont'
  • 'Geography: United States, Iowa, Michigan, Minnesota, North Dakota, South Dakota, Wisconsin, Minneapolis-St. Paul-Bloomington, MN-WI'
Short text
  • 'seat_name: District 7, District 2, District 24, District 5, District 3, District 6, District 17, District 1, District 9, District 13, District 50, District 15, District 16, District 11, District 4, District 10, District 53, District 12, District 8, District 39'
  • 'DEMEANOR_OF_PERSON_STOPPED: TERRORISM, OTHER, GRAND LARCENY AUTO, BURGLARY, CPW, NORMAL, PLEASANT, NERVOUS, CALM, ROBBERY, CRIMINAL MISCHIEF, WORRIED, MURDER, GRAND LARCENY, PETIT LARCENY, VERY CALM, QUESTIONED THE REASONING OF STOP, EXPLAINED AND SH, UPSET, IRRATE, ASSAULT'
  • 'notes: None, half sample, exit poll, question wording: positive/negative/neutral, question wording positive/negative, no polling 5/8; question wording positive/negative/neutral, full data provided by Craig Burnett, one third sample, question wording: positive/negative feeling, question wording: positive/negative , among those familiar'
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'
City Name
  • 'Facility.City: Dothan, Boaz, Florence, Opp, Luverne, Birmingham, Fort Payne, Alabaster, Sheffield, Ozark, Centre, Montgomery, Opelika, Wedowee, Tallassee, Cullman, Andalusia, Anniston, Huntsville, Gadsden'
  • 'recipient_city: ANCHORAGE, BIRMINGHAM, GUNTERSVILLE, HUNTSVILLE, BENTONVILLE, LITTLE ROCK, CONWAY, BENTON, MAUMELLE, ROGERS, JONESBORO, PHOENIX, TEMPE, SCOTTSDALE, CAVE CREEK, PHEONIX, CHANDLER, FLAGSTAFF, PARADISE VALLEY, SAFFORD'
  • "Capital: Kabul, Tirane, Algiers, Andorra la Vella, Luanda, Saint John's, Buenos Aires, Yerevan, Canberra, Vienna, Baku, Nassau, Manama, Dhaka, Bridgetown, Minsk, Brussels, Belmopan, Porto-Novo, Thimphu"
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'
  • 'Incident.Date.Day: 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23'
  • 'Date.Day: 26, 24, 31, 7, 14, 21, 28, 5, 12, 19, 2, 9, 16, 23, 30, 4, 11, 18, 25, 1'
Year
  • 'Year: 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013'
  • 'cycle: 2020, 2019, 2018'
  • 'Date.Year: 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009'
Month Number
  • 'Date.Month: 8, 3, 4, 5, 6, 7, 9, 10, 11, 12, 1, 2'
  • 'bibliography.publication.month: 6, 11, 3, 8, 1, 10, 7, 2, 4, 5, 9, 12'
  • 'Incident.Date.Month: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12'
Continents
  • 'Continent: Africa, South America, Asia, North America, Australia'
Integer
  • 'AVG.1: 72710, 70347, 69816, 71154, 65991, 69107, 70785, 71743, 69971, 69370, 68103, 65411, 67280, 73706, 68765, 68398, 68483, 69956, 71385, 66222'
  • 'death: 35305, 1604, 21226, 22676, 186428, 18925, 26005, 5123, 104190, 44230, 4849, 6753, 102230, 47300, 26348, 21910, 33765, 35518, 10768, 34025'
  • 'turn: 40, 35, 43, 34, 42, 44, 45, 31, 41, 46, 33, 51, 48, 39, 37, 36, 38, 32'
Numeric identifier
  • 'candidate_id: 15574, 15575, 13509, 13510, 15190, 14476, 14477, 15784, 14654, 14655, 15311, 14661, 14662, 15039, 14808, 14810, 14752, 14753, 15019, 15020'
  • 'Birthplace: 154746, 345512, 177841, 290849, 190024, 155725, 82043, 31450, 41079, 84188, 49076, 6147, 21065, 47884, 139859, 75546, 52967, 26345, 11015, 16390'
  • 'metadata.id: 1342, 1952, 11, 84, 5200, 76, 844, 74, 23, 2542, 2701, 1661, 1400, 4300, 98, 1080, 345, 1232, 174, 2600'
Price
  • 'Income Range: $0 - $30,000, $30,001 - $48,000, $48,001 - $75,000, $75,001 - $110,000, $110,000+'
Zip Code
  • 'zip_codes: nan, 12081.0, 10090.0, 12423.0, 12420.0'
  • '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'
  • 'recipient_zip: 995084442, 99503, 995163436, 352124572, 35216, 35976, 358021277, 352174710, 35203, 35233, 35805, 72716, 72201, 72035, 72015, 72223, 72019, 72113, 72758, 72227'
Categorical
  • 'location: None, Ground Plane, Above Ground'
  • 'population: lv, rv, v, a'
  • 'JURISDICTION_DESCRIPTION: PSB, Transit, Housing, Other, (null)'
Boolean
  • 'Factors.Mental-Illness: True'
  • 'chasing: False, True'
  • 'SEARCHED_FLAG: N, Y, ('
Day of Week
  • 'day: Sun, Sat, Thur, Fri'
  • 'DAY2: Monday, Wednesday, Tuesday, Friday, Saturday, Thursday, Sunday'
Percentage
  • 'PCT.2: 95.5, 96.5, 94.0, 99.4, 97.6, 100.9, 101.0, 101.1, 96.9, 98.0, 97.9, 98.1, 94.8, 100.7, 99.3, 97.1, 98.9, 98.7, 96.1, 99.7'
  • 'PCT.1: 99.3, 99.1, 96.2, 98.6, 98.8, 101.0, 99.6, 97.8, 96.7, 96.8, 98.1, 96.9, 98.0, 98.4, 98.5, 94.6, 101.4, 95.3, 99.8, 97.1'
  • 'Audience score %: 71.0, 81.0, 89.0, 64.0, 84.0, 80.0, 66.0, 51.0, 52.0, 47.0, 56.0, 61.0, 60.0, 76.0, 57.0, 63.0, 77.0, 58.0, 45.0, 83.0'
Postal Code
  • 'Code postal: 77700.0, nan'
Street Name
  • "Adresse: Adventureland, 10 Place d'Ariane, Fantasyland, None, Disneyland Paris, Unnamed Road, Discoveryland, 3 Rue de la Galmy, Boulevard du Grand Fossé, Liaison Douce, 24 Town Square, Les Pléiades, Frontierland, 5 Cours du Danube, Rue du BÅ“uf Agile, Avenue René Goscinny, 1998 Rue Georges Méliès, Boulevard du Parc, Town Square, Avenue Paul Séramy"
  • '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'
Month Name
  • 'month: Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec'
  • 'bibliography.publication.month name: June, November, March, August, January, October, July, February, April, May, September, December'
  • 'MONTH2: January, February, March, April, May, June, July, August, September, October, November, December'
Currency Code
  • 'cur_name: AFN, DZD, AOA, ARS, AMD, AZN, BDT, INR, BYR, XOF, BTN, BOB, BIF, KHR, XAF, CVE, CNY, COP, USD, CDF'
Full Name
  • 'artist.name: Abakanowicz, Magdalena, Abbey, Edwin Austin, Abbott, Berenice, Abbott, Lemuel Francis, Abrahams, Ivor, Absalon, Abts, Tomma, Acconci, Vito, Ackling, Roger, Ackroyd, Norman, Adam, Robert, Adams, Harry William, Adams, Norman, Adams, Robert, Adeney, Bernard, Adler, Jankel, Adshead, Mary, Adzak, Roy, Afro, Agar, Eileen'
  • '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'
  • "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."
URL
Place
  • 'Show.Theatre: Booth, Broadway, Ethel Barrymore, Palace, Belasco, Gershwin, Minskoff, Circle In The Square, Virginia, Criterion, Vivian Beaumont, Winter Garden, Plymouth, Richard Rodgers, Golden, Broadhurst, Imperial, Walter Kerr, St. James, Ambassador'
Coordinate
  • 'lat_long: POINT (-73.9561344937861 40.7940823884086), POINT (-73.9570437717691 40.794850940803904), POINT (-73.9768311751004 40.76671780725581), POINT (-73.9757249834141 40.7697032606755), POINT (-73.9593126695714 40.797533370163), POINT (-73.9565700386162 40.7902561000937), POINT (-73.9719735582476 40.7693045133578), POINT (-73.9602609920814 40.79428830455661), POINT (-73.9770718586754 40.7729752391435), POINT (-73.9596413903948 40.7903128889029), POINT (-73.9702676472613 40.7762126854894), POINT (-73.9683613516225 40.7725908847499), POINT (-73.9541201789795 40.7931811701082), POINT (-73.9582694312289 40.7917367820255), POINT (-73.9674285955293 40.7829723919744), POINT (-73.9722500196844 40.7742879599026), POINT (-73.9695063535333 40.7823507678183), POINT (-73.9532170504865 40.7919669739962), POINT (-73.9768603630674 40.7702795904962), POINT (-73.9706105896967 40.7698124821507)'
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"
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'
  • 'created_at: 12/17/20 21:39, 6/14/21 15:36, 11/2/20 09:02, 11/2/20 12:49, 11/2/20 19:02, 11/2/20 14:04, 11/2/20 17:37, 11/2/20 18:39, 11/2/20 18:40, 11/4/20 09:17, 11/4/20 10:29, 11/4/20 10:32, 11/4/20 10:38, 11/4/20 10:39, 11/28/20 21:14, 11/2/20 21:25, 11/2/20 21:32, 11/2/20 22:12, 11/2/20 23:30, 11/2/20 23:33'
Age
  • 'demographics.age: 40, 45, 58, 65, 70, 74, 0, 48, 77, 68, 56, 83, 71, 69, 44, 78, 73, 67, 53, 61'
  • 'Person.Age: 53, 47, 23, 32, 39, 18, 22, 35, 34, 25, 31, 41, 30, 37, 28, 42, 36, 49, 71, 33'
  • 'Age: Under 5 Years, 5 to 17 Years, 18 to 24 Years, 25 to 34 Years, 35 to 44 Years, 45 to 54 Years, 55 to 59 Years, 60 & 61 Years, 62 to 64 Years, 65 to 74 Years, 75 Years & Over'
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'
Marital status
  • 'never_married: 0, 1'
  • 'married: single, married'
AM/PM
  • 'shift: PM, AM'
Last Name
  • 'candidat: Bush, Perot, Clinton'
Location
  • "artist.birth.location: Polska, Philadelphia, United States, Springfield, United States, Leicestershire, United Kingdom, Wigan, United Kingdom, Tel Aviv-Yafo, Yisra'el, Kiel, Deutschland, New York, United States, Isleworth, United Kingdom, Leeds, United Kingdom, Kirkcaldy, United Kingdom, Worcester, United Kingdom, London, United Kingdom, Northampton, United Kingdom, Tuszyn, Polska, Reading, United Kingdom, Udine, Italia, Ayacucho, Argentina, Genve, Schweiz, Hmeenlinna, Suomi"
  • 'artist.death.location: None, London, United Kingdom, Monson, United States, Paris, France, Worcester, United Kingdom, Aldbourne, United Kingdom, Hampstead, United Kingdom, Zrich, Schweiz, New Haven, United States, Woodstock, United States, Musselburgh, United Kingdom, Maidstone, United Kingdom, Edinburgh, United Kingdom, Wallingford, United Kingdom, Barnes, United Kingdom, Wiesbaden, Deutschland, Los Angeles, Madrid, Espaa, Schweiz, Rennes, France'
  • 'Geography: United States, Virginia'
Abbreviation
  • 'bibliography.congress classifications: PR, PS, PZ,PR, PT, PZ,PS, E300, JC, PG, HQ, PQ, PR,PZ, PA,JC, PA, B, TJ, BS, HT, JK, PE, E011'
First Name
  • 'Top Name: Mary, Linda, Debra, Lisa, Michelle, Jennifer, Jessica, Samantha, Ashley, Hannah, Emily, Madison, Emma, Isabella, Sophia, Olivia, John, Robert, James, David'
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'

Evaluation

Metrics

Label Accuracy
all 0.7398

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/e5-base-v2-v3labels")
# Run inference
preds = model("variety: Western, Eastern")

Training Details

Training Set Metrics

Training set Min Median Max
Word count 2 22.2181 378
Label Training Sample Count
Categorical 8
Numeric 8
Timestamp 5
Date 8
Integer 8
Partial timestamp 3
Short text 8
Very short text 3
AM/PM 1
Boolean 8
City Name 4
Color 3
Company Name 1
Coordinate 1
Country ISO Code 3
Country Name 8
Currency Code 1
Day of Month 3
Day of Week 2
First Name 1
Floating Point Number 8
Full Name 8
Last Name 1
Latitude 4
License Plate 1
Longitude 4
Month Name 4
Month Number 4
Occupation 3
Postal Code 1
Price 1
Secondary Address 1
Slug 8
Street Address 1
Street Name 2
Time 1
U.S. State 8
U.S. State Abbreviation 6
URI 1
URL 8
Year 8
Zip Code 3
Likert scale 8
Gender 8
Letter grade 4
Race/Ethnicity 3
Marital status 2
Continents 1
Region 5
Age 3
Place 1
Abbreviation 1
Location 3
Structured field 6
Alphanumeric identifier 8
Percentage 7
ID 2
Numeric identifier 8

Training Hyperparameters

  • batch_size: (16, 16)
  • 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 0.1692 -
0.0139 50 0.3234 -
0.0278 100 0.2804 -
0.0417 150 0.2274 -
0.0556 200 0.1621 -
0.0695 250 0.1139 -
0.0834 300 0.0825 -
0.0972 350 0.0681 -
0.1111 400 0.0658 -
0.1250 450 0.0474 -
0.1389 500 0.0387 -
0.1528 550 0.0368 -
0.1667 600 0.0231 -
0.1806 650 0.029 -
0.1945 700 0.0242 -
0.2084 750 0.0248 -
0.2223 800 0.0238 -
0.2362 850 0.0171 -
0.2501 900 0.0158 -
0.2640 950 0.0182 -
0.2779 1000 0.0127 -
0.2917 1050 0.0141 -
0.3056 1100 0.009 -
0.3195 1150 0.0136 -
0.3334 1200 0.0095 -
0.3473 1250 0.0072 -
0.3612 1300 0.01 -
0.3751 1350 0.0074 -
0.3890 1400 0.0048 -
0.4029 1450 0.0042 -
0.4168 1500 0.0129 -
0.4307 1550 0.0058 -
0.4446 1600 0.0074 -
0.4585 1650 0.007 -
0.4724 1700 0.0028 -
0.4862 1750 0.0027 -
0.5001 1800 0.0041 -
0.5140 1850 0.0039 -
0.5279 1900 0.0015 -
0.5418 1950 0.0038 -
0.5557 2000 0.0013 -
0.5696 2050 0.0028 -
0.5835 2100 0.003 -
0.5974 2150 0.0033 -
0.6113 2200 0.0024 -
0.6252 2250 0.0032 -
0.6391 2300 0.0008 -
0.6530 2350 0.0008 -
0.6669 2400 0.0019 -
0.6807 2450 0.0009 -
0.6946 2500 0.0029 -
0.7085 2550 0.0018 -
0.7224 2600 0.0035 -
0.7363 2650 0.0011 -
0.7502 2700 0.0019 -
0.7641 2750 0.0022 -
0.7780 2800 0.0006 -
0.7919 2850 0.0008 -
0.8058 2900 0.0007 -
0.8197 2950 0.0017 -
0.8336 3000 0.0018 -
0.8475 3050 0.0013 -
0.8614 3100 0.0026 -
0.8752 3150 0.0024 -
0.8891 3200 0.0017 -
0.9030 3250 0.0009 -
0.9169 3300 0.0019 -
0.9308 3350 0.0038 -
0.9447 3400 0.004 -
0.9586 3450 0.0013 -
0.9725 3500 0.0009 -
0.9864 3550 0.0006 -
1.0 3599 - 0.1209
1.0003 3600 0.0017 -
1.0142 3650 0.0005 -
1.0281 3700 0.0005 -
1.0420 3750 0.0004 -
1.0558 3800 0.0023 -
1.0697 3850 0.0005 -
1.0836 3900 0.0004 -
1.0975 3950 0.0016 -
1.1114 4000 0.0004 -
1.1253 4050 0.0015 -
1.1392 4100 0.0005 -
1.1531 4150 0.0017 -
1.1670 4200 0.0004 -
1.1809 4250 0.001 -
1.1948 4300 0.0004 -
1.2087 4350 0.0015 -
1.2226 4400 0.0004 -
1.2365 4450 0.0012 -
1.2503 4500 0.0004 -
1.2642 4550 0.0016 -
1.2781 4600 0.0005 -
1.2920 4650 0.0017 -
1.3059 4700 0.0003 -
1.3198 4750 0.0007 -
1.3337 4800 0.0003 -
1.3476 4850 0.0016 -
1.3615 4900 0.0014 -
1.3754 4950 0.0004 -
1.3893 5000 0.0004 -
1.4032 5050 0.0004 -
1.4171 5100 0.0004 -
1.4310 5150 0.0004 -
1.4448 5200 0.0003 -
1.4587 5250 0.0005 -
1.4726 5300 0.0003 -
1.4865 5350 0.0016 -
1.5004 5400 0.0003 -
1.5143 5450 0.0003 -
1.5282 5500 0.0003 -
1.5421 5550 0.0003 -
1.5560 5600 0.0003 -
1.5699 5650 0.0003 -
1.5838 5700 0.0003 -
1.5977 5750 0.0003 -
1.6116 5800 0.0003 -
1.6255 5850 0.0003 -
1.6393 5900 0.0002 -
1.6532 5950 0.0002 -
1.6671 6000 0.0002 -
1.6810 6050 0.0002 -
1.6949 6100 0.0003 -
1.7088 6150 0.0011 -
1.7227 6200 0.0022 -
1.7366 6250 0.0027 -
1.7505 6300 0.006 -
1.7644 6350 0.0042 -
1.7783 6400 0.0038 -
1.7922 6450 0.0039 -
1.8061 6500 0.0007 -
1.8199 6550 0.0037 -
1.8338 6600 0.003 -
1.8477 6650 0.0037 -
1.8616 6700 0.0006 -
1.8755 6750 0.0005 -
1.8894 6800 0.0003 -
1.9033 6850 0.0014 -
1.9172 6900 0.0011 -
1.9311 6950 0.0004 -
1.9450 7000 0.0003 -
1.9589 7050 0.0004 -
1.9728 7100 0.0016 -
1.9867 7150 0.0002 -
2.0 7198 - 0.1146
2.0006 7200 0.0013 -
2.0144 7250 0.0002 -
2.0283 7300 0.0002 -
2.0422 7350 0.0003 -
2.0561 7400 0.0018 -
2.0700 7450 0.001 -
2.0839 7500 0.0003 -
2.0978 7550 0.0011 -
2.1117 7600 0.002 -
2.1256 7650 0.0004 -
2.1395 7700 0.0002 -
2.1534 7750 0.0013 -
2.1673 7800 0.0002 -
2.1812 7850 0.0011 -
2.1951 7900 0.0001 -
2.2089 7950 0.0002 -
2.2228 8000 0.0012 -
2.2367 8050 0.0002 -
2.2506 8100 0.0002 -
2.2645 8150 0.0008 -
2.2784 8200 0.0007 -
2.2923 8250 0.0014 -
2.3062 8300 0.0002 -
2.3201 8350 0.0002 -
2.3340 8400 0.0002 -
2.3479 8450 0.0007 -
2.3618 8500 0.001 -
2.3757 8550 0.0002 -
2.3896 8600 0.0014 -
2.4034 8650 0.0001 -
2.4173 8700 0.0003 -
2.4312 8750 0.0002 -
2.4451 8800 0.0001 -
2.4590 8850 0.0014 -
2.4729 8900 0.0002 -
2.4868 8950 0.0001 -
2.5007 9000 0.0001 -
2.5146 9050 0.0016 -
2.5285 9100 0.0002 -
2.5424 9150 0.0001 -
2.5563 9200 0.0002 -
2.5702 9250 0.0002 -
2.5841 9300 0.0001 -
2.5979 9350 0.0002 -
2.6118 9400 0.0001 -
2.6257 9450 0.0001 -
2.6396 9500 0.0002 -
2.6535 9550 0.0001 -
2.6674 9600 0.0001 -
2.6813 9650 0.0001 -
2.6952 9700 0.0001 -
2.7091 9750 0.0002 -
2.7230 9800 0.0001 -
2.7369 9850 0.001 -
2.7508 9900 0.0002 -
2.7647 9950 0.0001 -
2.7785 10000 0.0001 -
2.7924 10050 0.0001 -
2.8063 10100 0.0002 -
2.8202 10150 0.0001 -
2.8341 10200 0.0001 -
2.8480 10250 0.0008 -
2.8619 10300 0.0001 -
2.8758 10350 0.0001 -
2.8897 10400 0.0001 -
2.9036 10450 0.0002 -
2.9175 10500 0.0001 -
2.9314 10550 0.0001 -
2.9453 10600 0.0001 -
2.9592 10650 0.0006 -
2.9730 10700 0.0009 -
2.9869 10750 0.0003 -
3.0 10797 - 0.1168
3.0008 10800 0.0001 -
3.0147 10850 0.0001 -
3.0286 10900 0.0001 -
3.0425 10950 0.0001 -
3.0564 11000 0.0001 -
3.0703 11050 0.0001 -
3.0842 11100 0.0001 -
3.0981 11150 0.0008 -
3.1120 11200 0.0001 -
3.1259 11250 0.0001 -
3.1398 11300 0.0001 -
3.1537 11350 0.0006 -
3.1675 11400 0.0001 -
3.1814 11450 0.0001 -
3.1953 11500 0.0002 -
3.2092 11550 0.0001 -
3.2231 11600 0.0001 -
3.2370 11650 0.0001 -
3.2509 11700 0.0001 -
3.2648 11750 0.0001 -
3.2787 11800 0.0001 -
3.2926 11850 0.0001 -
3.3065 11900 0.0001 -
3.3204 11950 0.0001 -
3.3343 12000 0.0001 -
3.3482 12050 0.0001 -
3.3620 12100 0.0001 -
3.3759 12150 0.0001 -
3.3898 12200 0.0001 -
3.4037 12250 0.0001 -
3.4176 12300 0.0001 -
3.4315 12350 0.0001 -
3.4454 12400 0.0001 -
3.4593 12450 0.0001 -
3.4732 12500 0.0001 -
3.4871 12550 0.0001 -
3.5010 12600 0.0001 -
3.5149 12650 0.0001 -
3.5288 12700 0.0001 -
3.5427 12750 0.0001 -
3.5565 12800 0.0001 -
3.5704 12850 0.0001 -
3.5843 12900 0.0001 -
3.5982 12950 0.0001 -
3.6121 13000 0.0001 -
3.6260 13050 0.0001 -
3.6399 13100 0.0001 -
3.6538 13150 0.0001 -
3.6677 13200 0.0001 -
3.6816 13250 0.0001 -
3.6955 13300 0.0001 -
3.7094 13350 0.0001 -
3.7233 13400 0.0001 -
3.7371 13450 0.0001 -
3.7510 13500 0.0001 -
3.7649 13550 0.0001 -
3.7788 13600 0.0001 -
3.7927 13650 0.0001 -
3.8066 13700 0.0001 -
3.8205 13750 0.0001 -
3.8344 13800 0.0001 -
3.8483 13850 0.0001 -
3.8622 13900 0.0001 -
3.8761 13950 0.0001 -
3.8900 14000 0.0001 -
3.9039 14050 0.0001 -
3.9178 14100 0.0001 -
3.9316 14150 0.0001 -
3.9455 14200 0.0001 -
3.9594 14250 0.0001 -
3.9733 14300 0.0001 -
3.9872 14350 0.0001 -
4.0 14396 - 0.1199

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}
}
Downloads last month
1
Safetensors
Model size
109M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for quantisan/e5-base-v2-v3labels

Finetuned
(23)
this model

Evaluation results