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---
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: 'Category: Milk, Buttermilk, Kefir, Goat''s milk, Non-dairy milk, Soy milk,
Almond milk, Rice milk, Coconut milk, Yogurt, Chipotle dip, Dill dip, Onion dip,
Ranch dip, Spinach dip, Tzatziki dip, Vegetable dip, Yogurt parfait, Frozen yogurt,
Frozen yogurt sandwich'
- text: 'company.sector: Software, Finance, Communications, pharmaceuticals, technology,
Fashion, real estate, software, banking and insurance, groceries, construction/real
estate/banking, Oil refining, Oil refining, retail, retail, casinos, food
packaging, cars, cosmetics, None'
- text: 'variety: Western, Eastern'
- text: 'Data.Lycopene: 0, 1, 300, 7271, 6399, 4601, 4123, 1523, 1422, 1351, 11, 816,
819, 812, 1001, 769, 1365, 97, 21, 34'
- text: 'Date.Month: 8, 3, 4, 5, 6, 7, 9, 10, 11, 12, 1, 2'
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: 0.7629716981132075
name: Accuracy
---
# SetFit with sentence-transformers/paraphrase-MiniLM-L3-v2
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-MiniLM-L3-v2](https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L3-v2) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) 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](https://www.sbert.net) with contrastive learning.
2. 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](https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L3-v2)
- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
- **Maximum Sequence Length:** 128 tokens
- **Number of Classes:** 53 classes
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### Model Sources
- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
### Model Labels
| Label | Examples |
|:------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Integer | <ul><li>'quality: 5, 6, 7, 4, 8, 3'</li><li>'trunk: 11, 12, 16, 20, 21, 10, 17, 13, 9, 7, 8, 22, 18, 15, 23, 14, 6, 5'</li><li>'Completions: 589, 112, 114, 199, 156, 239, 451, 187, 252, 395, 682, 1, 1228, 93, 315, 150, 80, 92, 233, 406'</li></ul> |
| Country Name | <ul><li>'Nationality: Portugal, Argentina, Brazil, Uruguay, Germany, Poland, Spain, Belgium, Chile, Croatia, Wales, Italy, Slovenia, France, Gabon, Sweden, Netherlands, Denmark, Slovakia, England'</li><li>'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'</li><li>'Nation: Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, The Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan'</li></ul> |
| License Plate | <ul><li>'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'</li></ul> |
| Date | <ul><li>'Incident.Date.Full: 2015/01/02, 2015/01/03, 2015/01/04, 2015/01/05, 2015/01/06, 2015/01/07, 2015/01/08, 2015/01/09, 2015/01/11, 2015/01/13, 2015/01/14, 2015/01/15, 2015/01/16, 2015/01/17, 2015/01/18, 2015/01/19, 2015/01/20, 2015/01/21, 2015/01/22, 2015/01/23'</li><li>'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'</li><li>'week_ended: 2021-08-28, 2021-08-21, 2021-08-14, 2021-08-07, 2021-07-31, 2021-07-24, 2021-07-17, 2021-07-10, 2021-07-03, 2021-06-26, 2021-06-19, 2021-06-12, 2021-06-05, 2021-05-29, 2021-05-22, 2021-05-15, 2021-05-08, 2021-05-01, 2021-04-24, 2021-04-17'</li></ul> |
| Latitude | <ul><li>'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'</li><li>'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'</li><li>'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'</li></ul> |
| Month Number | <ul><li>'bibliography.publication.month: 6, 11, 3, 8, 1, 10, 7, 2, 4, 5, 9, 12'</li><li>'Date.Month: 8, 3, 4, 5, 6, 7, 9, 10, 11, 12, 1, 2'</li><li>'Incident.Date.Month: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12'</li></ul> |
| Floating Point Number | <ul><li>'femwhite: 6262128.0, 6785226.0, 6960988.0, 6879090.0, 6388969.0, 6655571.0, 7328058.0, 8487223.0, 8634083.0, 7955003.0, 7190359.0, 5691567.0, 4653172.0, 4286302.0, 4240992.0, 3833722.0, 2764852.0'</li><li>'Total Population MOE Appx: 93589.07647025918, 97743.48311569727, 102875.52676728423, 100180.67827181323, 91225.48461689966, 84927.02484353623, 74086.5329139754, 64054.081534081255, 58510.64119755533, 49482.37049442148, 50209.88701800759, 34985.37698863254, 35444.72186612619, 31511.029844047032, 25723.46796958681, 26258.43669569568, 23366.799224435217, 18833.469882408906, 17592.145498006077, 15373.85201819406'</li><li>'chlorides: 0.076, 0.098, 0.092, 0.075, 0.069, 0.065, 0.073, 0.071, 0.097, 0.089, 0.114, 0.176, 0.17, 0.368, 0.086, 0.341, 0.077, 0.082, 0.106, 0.084'</li></ul> |
| Time | <ul><li>'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'</li></ul> |
| Place | <ul><li>'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'</li></ul> |
| Full Name | <ul><li>'Person.Name: Tim Elliot, Lewis Lee Lembke, John Paul Quintero, Matthew Hoffman, Michael Rodriguez, Kenneth Joe Brown, Kenneth Arnold Buck, Brock Nichols, Autumn Steele, Leslie Sapp III, Patrick Wetter, Ron Sneed, Hashim Hanif Ibn Abdul-Rasheed, Nicholas Ryan Brickman, Omarr Julian Maximillian Jackson, Loren Simpson, James Dudley Barker, Artago Damon Howard, Thomas Hamby, Jimmy Foreman'</li><li>'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'</li><li>'candidate_name: Abigail A. Spanberger, Nicholas J. Freitas, Kara Eastman, Don Bacon, Tyler Schaeffer, Jill Schupp, Ann Wagner, Martin Schulte, Dana Balter, John Katko, Steve Williams, Christina Hale, Victoria Spartz, Kenneth Tucker, Joyce Ann Elliott, French Hill, Jared Forrest Golden, Dale John Crafts, Marie Newman, Mike Fricilone'</li></ul> |
| U.S. State Abbreviation | <ul><li>'Incident.Location.State: WA, OR, KS, CA, CO, OK, AZ, IA, PA, TX, OH, LA, MT, UT, AR, IL, NV, NM, MN, MO'</li><li>'state2: AL, AK, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KS, KY, LA, ME, MD'</li><li>'State: AK, AL, AR, AZ, CA, CO, CT, DC, DE, FL, GA, HI, IA, ID, IL, IN, KS, KY, LA, MA'</li></ul> |
| Price | <ul><li>'Income Range: $0 - $30,000, $30,001 - $48,000, $48,001 - $75,000, $75,001 - $110,000, $110,000+'</li></ul> |
| U.S. State | <ul><li>'state: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland'</li><li>'Geography: United States, Iowa, Michigan, Minnesota, North Dakota, South Dakota, Wisconsin, Minneapolis-St. Paul-Bloomington, MN-WI'</li><li>'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'</li></ul> |
| Gender | <ul><li>"Gender: Men's, Women's"</li><li>'sex: Male, Female'</li><li>'gender: Female, Male'</li></ul> |
| Longitude | <ul><li>'long: -73.9561344937861, -73.9570437717691, -73.9768311751004, -73.9757249834141, -73.9593126695714, -73.9565700386162, -73.9719735582476, -73.9602609920814, -73.9770718586754, -73.9596413903948, -73.9702676472613, -73.9683613516225, -73.9541201789795, -73.9582694312289, -73.9674285955293, -73.9722500196844, -73.9695063535333, -73.9532170504865, -73.9768603630674, -73.9706105896967'</li><li>'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'</li><li>'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'</li></ul> |
| URL | <ul><li>'metadata.url: https://www.gutenberg.org/ebooks/1342, https://www.gutenberg.org/ebooks/1952, https://www.gutenberg.org/ebooks/11, https://www.gutenberg.org/ebooks/84, https://www.gutenberg.org/ebooks/5200, https://www.gutenberg.org/ebooks/76, https://www.gutenberg.org/ebooks/844, https://www.gutenberg.org/ebooks/74, https://www.gutenberg.org/ebooks/23, https://www.gutenberg.org/ebooks/2542, https://www.gutenberg.org/ebooks/2701, https://www.gutenberg.org/ebooks/1661, https://www.gutenberg.org/ebooks/1400, https://www.gutenberg.org/ebooks/4300, https://www.gutenberg.org/ebooks/98, https://www.gutenberg.org/ebooks/1080, https://www.gutenberg.org/ebooks/345, https://www.gutenberg.org/ebooks/1232, https://www.gutenberg.org/ebooks/174, https://www.gutenberg.org/ebooks/2600'</li><li>'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'</li><li>'data.url: http://www.tate.org.uk/art/artworks/abakanowicz-backs-t12981, http://www.tate.org.uk/art/artworks/abbey-illustration-to-judith-shakespeare-n03992, http://www.tate.org.uk/art/artworks/abbott-tri-boro-barber-shop-p13100, http://www.tate.org.uk/art/artworks/abbott-portrait-of-the-engraver-francesco-bartolozzi-t01067, http://www.tate.org.uk/art/artworks/abrahams-lady-in-niche-t03369, http://www.tate.org.uk/art/artworks/absalon-assassinations-t07227, http://www.tate.org.uk/art/artworks/abts-zebe-t13592, http://www.tate.org.uk/art/artworks/acconci-transference-zone-t13178, http://www.tate.org.uk/art/artworks/ackling-five-sunsets-in-one-hour-t03562, http://www.tate.org.uk/art/artworks/ackroyd-cartmel-fell-p77815, http://www.tate.org.uk/art/artworks/adam-composition-river-in-a-gorge-t09843, http://www.tate.org.uk/art/artworks/adams-winters-sleep-n01838, http://www.tate.org.uk/art/artworks/adams-christs-cross-and-adams-tree-t05820, http://www.tate.org.uk/art/artworks/adams-space-construction-with-a-spiral-t07034, http://www.tate.org.uk/art/artworks/adeney-toy-sailing-boats-the-round-pond-n04568, http://www.tate.org.uk/art/artworks/adler-the-mutilated-t00372, http://www.tate.org.uk/art/artworks/adshead-the-cruise-t07229, http://www.tate.org.uk/art/artworks/adzak-cut-bottle-relief-t00875, http://www.tate.org.uk/art/artworks/afro-the-struggle-t00017, http://www.tate.org.uk/art/artworks/agar-figures-in-a-garden-t06749'</li></ul> |
| Day of Week | <ul><li>'day: Sun, Sat, Thur, Fri'</li><li>'DAY2: Monday, Wednesday, Tuesday, Friday, Saturday, Thursday, Sunday'</li></ul> |
| Slug | <ul><li>'Slug Geography: united-states, virginia'</li><li>'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'</li><li>'Slug CIP: liberal-arts-sciences'</li></ul> |
| Timestamp | <ul><li>'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'</li><li>'date: 2001-01-02 00:00:00, 2001-01-03 00:00:00, 2001-01-04 00:00:00, 2001-01-05 00:00:00, 2001-01-08 00:00:00, 2001-01-09 00:00:00, 2001-01-10 00:00:00, 2001-01-11 00:00:00, 2001-01-12 00:00:00, 2001-01-16 00:00:00, 2001-01-17 00:00:00, 2001-01-18 00:00:00, 2001-01-19 00:00:00, 2001-01-22 00:00:00, 2001-01-23 00:00:00, 2001-01-24 00:00:00, 2001-01-25 00:00:00, 2001-01-26 00:00:00, 2001-01-29 00:00:00, 2001-01-30 00:00:00'</li><li>'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'</li></ul> |
| Coordinate | <ul><li>'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)'</li></ul> |
| Likert scale | <ul><li>'Procedure.Hip Knee.Quality: Average, Unknown, Better, Worse'</li><li>'Rating.Experience: Below, Same, None, Above'</li><li>'Procedure.Heart Failure.Quality: Average, Worse, Unknown, Better'</li></ul> |
| Categorical | <ul><li>'species: setosa, versicolor, virginica'</li><li>'stage: general'</li><li>'color: E, I, J, H, F, G, D'</li></ul> |
| Secondary Address | <ul><li>'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'</li></ul> |
| Year | <ul><li>'Year: 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979'</li><li>'Year: 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013'</li><li>'Date.Year: 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009'</li></ul> |
| Zip Code | <ul><li>'zip_codes: nan, 12081.0, 10090.0, 12423.0, 12420.0'</li><li>'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'</li><li>'recipient_zip: 995084442, 99503, 995163436, 352124572, 35216, 35976, 358021277, 352174710, 35203, 35233, 35805, 72716, 72201, 72035, 72015, 72223, 72019, 72113, 72758, 72227'</li></ul> |
| Region | <ul><li>'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'</li><li>'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'</li><li>'region: South, West, NE, N Cntrl'</li></ul> |
| AM/PM | <ul><li>'shift: PM, AM'</li></ul> |
| Race/Ethnicity | <ul><li>'Person.Race: Asian, White, Hispanic, African American, Other, Unknown, Native American'</li><li>'SUSPECT_RACE_DESCRIPTION: (null), WHITE, BLACK HISPANIC, BLACK, WHITE HISPANIC, ASIAN/PAC.ISL, AMER IND, MALE'</li><li>'race: black, white, other'</li></ul> |
| Street Name | <ul><li>'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'</li><li>"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 Bœuf Agile, Avenue René Goscinny, 1998 Rue Georges Méliès, Boulevard du Parc, Town Square, Avenue Paul Séramy"</li></ul> |
| Day of Month | <ul><li>'bibliography.publication.day: 1, 17, 16, 20, 29, 10, 14, 11, 9, 18, 19, 22, 25, 15, 6, 28, 27, 2, 12, 21'</li><li>'Date.Day: 26, 24, 31, 7, 14, 21, 28, 5, 12, 19, 2, 9, 16, 23, 30, 4, 11, 18, 25, 1'</li><li>'Incident.Date.Day: 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23'</li></ul> |
| Boolean | <ul><li>'ID Workforce Status: True'</li><li>'nationwide_batch: False'</li><li>'PHYSICAL_FORCE_RESTRAINT_USED_FLAG: (null), Y'</li></ul> |
| Color | <ul><li>'highlight_fur_color: None, Cinnamon, White, Gray, Cinnamon, White, Gray, White, Black, Cinnamon, White, Black, Black, White, Black, Cinnamon, Gray, Black'</li><li>'color: Yellow, Black, White'</li><li>'primary_fur_color: None, Gray, Cinnamon, Black'</li></ul> |
| Location | <ul><li>'Geography: United States, Virginia'</li><li>"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"</li><li>'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'</li></ul> |
| Last Name | <ul><li>'candidat: Bush, Perot, Clinton'</li></ul> |
| Company Name | <ul><li>"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"</li></ul> |
| Street Address | <ul><li>'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'</li></ul> |
| Short text | <ul><li>'make: AMC Concord, AMC Pacer, AMC Spirit, Buick Century, Buick Electra, Buick LeSabre, Buick Opel, Buick Regal, Buick Riviera, Buick Skylark, Cad. Deville, Cad. Eldorado, Cad. Seville, Chev. Chevette, Chev. Impala, Chev. Malibu, Chev. Monte Carlo, Chev. Monza, Chev. Nova, Dodge Colt'</li><li>'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'</li><li>'memo_text: IN KIND: FACILITY RENTAL, None, IN KIND: BUMPER STICKERS SIGNS AND BUTTONS, IN KIND: BILLBOARD ADVERTISING, IN KIND: CATERING, IN KIND: PHOTOGRAPHY, IN KIND: AIR TRAVEL, IN KIND: PHOTOGRAPHY SERVICES, IN KIND: FACILITY RENTAL/CATERING, IN KIND: CAR RENTAL PARADE TICKET BANNER, IN KIND: CAMPAIGN SIGNS, IN KIND: OFFICE SPACE, IN KIND: BOOTH SPACE AT INDIANA STATE FAIR, IN KIND: TRAVEL, IN KIND: CHARTER BUS, IN KIND: SIGNAGE, IN KIND: EMAIL LIST, IN KIND: AIRFARE, IN KIND: TABLES, IN KIND: LODGING'</li></ul> |
| Occupation | <ul><li>'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'</li><li>'occupation: Operatives, Craftsmen, Sales, Other, Managers/admin, Professional/technical, Clerical/unskilled, Laborers, Transport, Service, nan, Household workers, Farm laborers, Farmers'</li><li>'Detailed Occupation: Other managers, Cashiers, Retail salespersons, Driver/sales workers & truck drivers, Registered nurses'</li></ul> |
| Very short text | <ul><li>'above_ground_sighter_measurement: None, FALSE, 4, 3, 30, 10, 6, 24, 8, 25, 5, 50, 70, 12, 2, 20, 7, 13, 15, 28'</li><li>'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?'</li><li>'status: N, Y, REMOVE, None, 1, ?, H, R, M, T'</li></ul> |
| Numeric | <ul><li>'cat_idx: 1, 2, 3'</li><li>'solutions: 1, 2, 3'</li><li>'metadata.formats.total: 8, 7, 6, 9, 5, 11, 10, 12, 3, 4'</li></ul> |
| URI | <ul><li>'data.thumbnail: http://www.tate.org.uk/art/images/work/T/T12/T12981_8.jpg, http://www.tate.org.uk/art/images/work/N/N03/N03992_8.jpg, None, http://www.tate.org.uk/art/images/work/T/T01/T01067_8.jpg, http://www.tate.org.uk/art/images/work/T/T03/T03369_8.jpg, http://www.tate.org.uk/art/images/work/T/T13/T13592_8.jpg, http://www.tate.org.uk/art/images/work/T/T03/T03562_8.jpg, http://www.tate.org.uk/art/images/work/P/P77/P77815_8.jpg, http://www.tate.org.uk/art/images/work/T/T09/T09843_8.jpg, http://www.tate.org.uk/art/images/work/T/T05/T05820_8.jpg, http://www.tate.org.uk/art/images/work/T/T07/T07034_8.jpg, http://www.tate.org.uk/art/images/work/T/T00/T00372_8.jpg, http://www.tate.org.uk/art/images/work/T/T07/T07229_8.jpg, http://www.tate.org.uk/art/images/work/T/T06/T06749_8.jpg, http://www.tate.org.uk/art/images/work/T/T02/T02351_8.jpg, http://www.tate.org.uk/art/images/work/T/T13/T13408_8.jpg, http://www.tate.org.uk/art/images/work/T/T06/T06680_8.jpg, http://www.tate.org.uk/art/images/work/T/T12/T12215_8.jpg, http://www.tate.org.uk/art/images/work/T/T07/T07626_8.jpg, http://www.tate.org.uk/art/images/work/P/P77/P77242_8.jpg'</li></ul> |
| Letter grade | <ul><li>'fte_grade: B+, B, B/C, A, A-, None, C, A/B, B-, A+, C/D'</li><li>'fte_grade: B+, B, B/C, A, A-, None, C, A/B, B-, A+, C/D'</li><li>'fte_grade: B/C, B-, A-, A, B+, B, C/D, A/B, A+, C+, None, F'</li></ul> |
| Month Name | <ul><li>'month: Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec'</li><li>'Month: JAN, FEB, MAR, APR, MAY, JUN, JUL, AUG, SEP, OCT, NOV, DEC'</li><li>'bibliography.publication.month name: June, November, March, August, January, October, July, February, April, May, September, December'</li></ul> |
| Age | <ul><li>'Person.Age: 53, 47, 23, 32, 39, 18, 22, 35, 34, 25, 31, 41, 30, 37, 28, 42, 36, 49, 71, 33'</li><li>'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'</li><li>'demographics.age: 40, 45, 58, 65, 70, 74, 0, 48, 77, 68, 56, 83, 71, 69, 44, 78, 73, 67, 53, 61'</li></ul> |
| Partial timestamp | <ul><li>'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'</li><li>'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'</li><li>'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'</li></ul> |
| Abbreviation | <ul><li>'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'</li></ul> |
| Country ISO Code | <ul><li>"Runner-up Nationality (Men's): None, USA, BRA, AUS, RSA, FRA, CND, RUS, GBR, BEL, GER, ESP, NED, POL, ARG, CZE, YUG, TCH, URS"</li><li>'Runner-up Nationality: AUS, GBR, NZL, FRA, USA, RSA, CZE, ARG, GER, SUI, ESP, CRO, ROM, DEN, TCH, URS, CZ, SRB, CND, SWE'</li><li>'Champion Nationality: AUS, FRA, GBR, NZL, USA, SRB, SUI, SWE, CZE, ESP, GER, NED, CRO, BRA, RUS'</li></ul> |
| City Name | <ul><li>'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'</li><li>'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'</li><li>'Facility.City: Dothan, Boaz, Florence, Opp, Luverne, Birmingham, Fort Payne, Alabaster, Sheffield, Ozark, Centre, Montgomery, Opelika, Wedowee, Tallassee, Cullman, Andalusia, Anniston, Huntsville, Gadsden'</li></ul> |
| Continents | <ul><li>'Continent: Africa, South America, Asia, North America, Australia'</li></ul> |
| Postal Code | <ul><li>'Code postal: 77700.0, nan'</li></ul> |
| Marital status | <ul><li>'married: single, married'</li><li>'never_married: 0, 1'</li></ul> |
| First Name | <ul><li>'Top Name: Mary, Linda, Debra, Lisa, Michelle, Jennifer, Jessica, Samantha, Ashley, Hannah, Emily, Madison, Emma, Isabella, Sophia, Olivia, John, Robert, James, David'</li></ul> |
| Currency Code | <ul><li>'cur_name: AFN, DZD, AOA, ARS, AMD, AZN, BDT, INR, BYR, XOF, BTN, BOB, BIF, KHR, XAF, CVE, CNY, COP, USD, CDF'</li></ul> |
## Evaluation
### Metrics
| Label | Accuracy |
|:--------|:---------|
| **all** | 0.7630 |
## Uses
### Direct Use for Inference
First install the SetFit library:
```bash
pip install setfit
```
Then you can load this model and run inference.
```python
from setfit import SetFitModel
# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("quantisan/paraphrase-MiniLM-L3-v2-93dataset-v2labels")
# Run inference
preds = model("variety: Western, Eastern")
```
<!--
### Downstream Use
*List how someone could finetune this model on their own dataset.*
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
<!--
## Bias, Risks and Limitations
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->
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### Recommendations
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->
## Training Details
### Training Set Metrics
| Training set | Min | Median | Max |
|:-------------|:----|:--------|:----|
| Word count | 2 | 22.1604 | 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 |
### 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 |
|:------:|:-----:|:-------------:|:---------------:|
| 0.0002 | 1 | 0.1497 | - |
| 0.0092 | 50 | 0.1834 | - |
| 0.0183 | 100 | 0.1917 | - |
| 0.0275 | 150 | 0.1712 | - |
| 0.0366 | 200 | 0.1505 | - |
| 0.0458 | 250 | 0.146 | - |
| 0.0549 | 300 | 0.1465 | - |
| 0.0641 | 350 | 0.1297 | - |
| 0.0732 | 400 | 0.1238 | - |
| 0.0824 | 450 | 0.111 | - |
| 0.0916 | 500 | 0.1035 | - |
| 0.1007 | 550 | 0.1008 | - |
| 0.1099 | 600 | 0.0914 | - |
| 0.1190 | 650 | 0.0869 | - |
| 0.1282 | 700 | 0.0792 | - |
| 0.1373 | 750 | 0.0712 | - |
| 0.1465 | 800 | 0.0709 | - |
| 0.1556 | 850 | 0.0808 | - |
| 0.1648 | 900 | 0.0659 | - |
| 0.1740 | 950 | 0.0611 | - |
| 0.1831 | 1000 | 0.0611 | - |
| 0.1923 | 1050 | 0.0607 | - |
| 0.2014 | 1100 | 0.0611 | - |
| 0.2106 | 1150 | 0.0507 | - |
| 0.2197 | 1200 | 0.0577 | - |
| 0.2289 | 1250 | 0.0508 | - |
| 0.2381 | 1300 | 0.0399 | - |
| 0.2472 | 1350 | 0.0442 | - |
| 0.2564 | 1400 | 0.0516 | - |
| 0.2655 | 1450 | 0.0441 | - |
| 0.2747 | 1500 | 0.0472 | - |
| 0.2838 | 1550 | 0.0284 | - |
| 0.2930 | 1600 | 0.0492 | - |
| 0.3021 | 1650 | 0.035 | - |
| 0.3113 | 1700 | 0.0338 | - |
| 0.3205 | 1750 | 0.0286 | - |
| 0.3296 | 1800 | 0.0296 | - |
| 0.3388 | 1850 | 0.0328 | - |
| 0.3479 | 1900 | 0.0277 | - |
| 0.3571 | 1950 | 0.0269 | - |
| 0.3662 | 2000 | 0.0262 | - |
| 0.3754 | 2050 | 0.0311 | - |
| 0.3845 | 2100 | 0.0277 | - |
| 0.3937 | 2150 | 0.022 | - |
| 0.4029 | 2200 | 0.0216 | - |
| 0.4120 | 2250 | 0.0213 | - |
| 0.4212 | 2300 | 0.0231 | - |
| 0.4303 | 2350 | 0.0255 | - |
| 0.4395 | 2400 | 0.02 | - |
| 0.4486 | 2450 | 0.0181 | - |
| 0.4578 | 2500 | 0.0196 | - |
| 0.4669 | 2550 | 0.0182 | - |
| 0.4761 | 2600 | 0.0199 | - |
| 0.4853 | 2650 | 0.0171 | - |
| 0.4944 | 2700 | 0.0171 | - |
| 0.5036 | 2750 | 0.0169 | - |
| 0.5127 | 2800 | 0.0161 | - |
| 0.5219 | 2850 | 0.0104 | - |
| 0.5310 | 2900 | 0.0133 | - |
| 0.5402 | 2950 | 0.0137 | - |
| 0.5493 | 3000 | 0.0241 | - |
| 0.5585 | 3050 | 0.0156 | - |
| 0.5677 | 3100 | 0.0155 | - |
| 0.5768 | 3150 | 0.0158 | - |
| 0.5860 | 3200 | 0.0165 | - |
| 0.5951 | 3250 | 0.0141 | - |
| 0.6043 | 3300 | 0.0129 | - |
| 0.6134 | 3350 | 0.0129 | - |
| 0.6226 | 3400 | 0.0103 | - |
| 0.6318 | 3450 | 0.011 | - |
| 0.6409 | 3500 | 0.0117 | - |
| 0.6501 | 3550 | 0.0128 | - |
| 0.6592 | 3600 | 0.0125 | - |
| 0.6684 | 3650 | 0.0138 | - |
| 0.6775 | 3700 | 0.0101 | - |
| 0.6867 | 3750 | 0.0123 | - |
| 0.6958 | 3800 | 0.0127 | - |
| 0.7050 | 3850 | 0.0088 | - |
| 0.7142 | 3900 | 0.0097 | - |
| 0.7233 | 3950 | 0.0078 | - |
| 0.7325 | 4000 | 0.0056 | - |
| 0.7416 | 4050 | 0.0096 | - |
| 0.7508 | 4100 | 0.0114 | - |
| 0.7599 | 4150 | 0.0105 | - |
| 0.7691 | 4200 | 0.0101 | - |
| 0.7782 | 4250 | 0.0077 | - |
| 0.7874 | 4300 | 0.0104 | - |
| 0.7966 | 4350 | 0.007 | - |
| 0.8057 | 4400 | 0.0112 | - |
| 0.8149 | 4450 | 0.008 | - |
| 0.8240 | 4500 | 0.0063 | - |
| 0.8332 | 4550 | 0.0153 | - |
| 0.8423 | 4600 | 0.0081 | - |
| 0.8515 | 4650 | 0.007 | - |
| 0.8606 | 4700 | 0.0052 | - |
| 0.8698 | 4750 | 0.0054 | - |
| 0.8790 | 4800 | 0.0063 | - |
| 0.8881 | 4850 | 0.0131 | - |
| 0.8973 | 4900 | 0.0086 | - |
| 0.9064 | 4950 | 0.0086 | - |
| 0.9156 | 5000 | 0.008 | - |
| 0.9247 | 5050 | 0.0097 | - |
| 0.9339 | 5100 | 0.0081 | - |
| 0.9431 | 5150 | 0.0052 | - |
| 0.9522 | 5200 | 0.008 | - |
| 0.9614 | 5250 | 0.0055 | - |
| 0.9705 | 5300 | 0.0048 | - |
| 0.9797 | 5350 | 0.0055 | - |
| 0.9888 | 5400 | 0.0064 | - |
| 0.9980 | 5450 | 0.0043 | - |
| 1.0 | 5461 | - | 0.0926 |
| 1.0071 | 5500 | 0.0064 | - |
| 1.0163 | 5550 | 0.0079 | - |
| 1.0255 | 5600 | 0.0037 | - |
| 1.0346 | 5650 | 0.0045 | - |
| 1.0438 | 5700 | 0.0072 | - |
| 1.0529 | 5750 | 0.0055 | - |
| 1.0621 | 5800 | 0.0046 | - |
| 1.0712 | 5850 | 0.0039 | - |
| 1.0804 | 5900 | 0.0063 | - |
| 1.0895 | 5950 | 0.0071 | - |
| 1.0987 | 6000 | 0.005 | - |
| 1.1079 | 6050 | 0.0066 | - |
| 1.1170 | 6100 | 0.0041 | - |
| 1.1262 | 6150 | 0.0056 | - |
| 1.1353 | 6200 | 0.0063 | - |
| 1.1445 | 6250 | 0.0057 | - |
| 1.1536 | 6300 | 0.004 | - |
| 1.1628 | 6350 | 0.0058 | - |
| 1.1719 | 6400 | 0.0067 | - |
| 1.1811 | 6450 | 0.0058 | - |
| 1.1903 | 6500 | 0.0081 | - |
| 1.1994 | 6550 | 0.0062 | - |
| 1.2086 | 6600 | 0.0062 | - |
| 1.2177 | 6650 | 0.0034 | - |
| 1.2269 | 6700 | 0.0031 | - |
| 1.2360 | 6750 | 0.0048 | - |
| 1.2452 | 6800 | 0.006 | - |
| 1.2543 | 6850 | 0.0054 | - |
| 1.2635 | 6900 | 0.007 | - |
| 1.2727 | 6950 | 0.0064 | - |
| 1.2818 | 7000 | 0.0055 | - |
| 1.2910 | 7050 | 0.0049 | - |
| 1.3001 | 7100 | 0.0063 | - |
| 1.3093 | 7150 | 0.0044 | - |
| 1.3184 | 7200 | 0.0063 | - |
| 1.3276 | 7250 | 0.003 | - |
| 1.3368 | 7300 | 0.0049 | - |
| 1.3459 | 7350 | 0.0047 | - |
| 1.3551 | 7400 | 0.0043 | - |
| 1.3642 | 7450 | 0.0023 | - |
| 1.3734 | 7500 | 0.0025 | - |
| 1.3825 | 7550 | 0.0047 | - |
| 1.3917 | 7600 | 0.0027 | - |
| 1.4008 | 7650 | 0.0036 | - |
| 1.4100 | 7700 | 0.0026 | - |
| 1.4192 | 7750 | 0.0019 | - |
| 1.4283 | 7800 | 0.0048 | - |
| 1.4375 | 7850 | 0.0047 | - |
| 1.4466 | 7900 | 0.0041 | - |
| 1.4558 | 7950 | 0.0073 | - |
| 1.4649 | 8000 | 0.0023 | - |
| 1.4741 | 8050 | 0.0054 | - |
| 1.4832 | 8100 | 0.0042 | - |
| 1.4924 | 8150 | 0.0078 | - |
| 1.5016 | 8200 | 0.0063 | - |
| 1.5107 | 8250 | 0.0033 | - |
| 1.5199 | 8300 | 0.0055 | - |
| 1.5290 | 8350 | 0.0043 | - |
| 1.5382 | 8400 | 0.0027 | - |
| 1.5473 | 8450 | 0.0021 | - |
| 1.5565 | 8500 | 0.0022 | - |
| 1.5656 | 8550 | 0.0063 | - |
| 1.5748 | 8600 | 0.0049 | - |
| 1.5840 | 8650 | 0.0049 | - |
| 1.5931 | 8700 | 0.0057 | - |
| 1.6023 | 8750 | 0.0035 | - |
| 1.6114 | 8800 | 0.0022 | - |
| 1.6206 | 8850 | 0.0029 | - |
| 1.6297 | 8900 | 0.0062 | - |
| 1.6389 | 8950 | 0.0022 | - |
| 1.6480 | 9000 | 0.0047 | - |
| 1.6572 | 9050 | 0.0024 | - |
| 1.6664 | 9100 | 0.0053 | - |
| 1.6755 | 9150 | 0.0021 | - |
| 1.6847 | 9200 | 0.0029 | - |
| 1.6938 | 9250 | 0.0031 | - |
| 1.7030 | 9300 | 0.0024 | - |
| 1.7121 | 9350 | 0.0034 | - |
| 1.7213 | 9400 | 0.0021 | - |
| 1.7305 | 9450 | 0.0025 | - |
| 1.7396 | 9500 | 0.0023 | - |
| 1.7488 | 9550 | 0.0029 | - |
| 1.7579 | 9600 | 0.0025 | - |
| 1.7671 | 9650 | 0.0021 | - |
| 1.7762 | 9700 | 0.0019 | - |
| 1.7854 | 9750 | 0.0034 | - |
| 1.7945 | 9800 | 0.0016 | - |
| 1.8037 | 9850 | 0.0019 | - |
| 1.8129 | 9900 | 0.0024 | - |
| 1.8220 | 9950 | 0.002 | - |
| 1.8312 | 10000 | 0.0021 | - |
| 1.8403 | 10050 | 0.0061 | - |
| 1.8495 | 10100 | 0.0019 | - |
| 1.8586 | 10150 | 0.0014 | - |
| 1.8678 | 10200 | 0.0021 | - |
| 1.8769 | 10250 | 0.0031 | - |
| 1.8861 | 10300 | 0.002 | - |
| 1.8953 | 10350 | 0.0014 | - |
| 1.9044 | 10400 | 0.0015 | - |
| 1.9136 | 10450 | 0.0014 | - |
| 1.9227 | 10500 | 0.0018 | - |
| 1.9319 | 10550 | 0.0014 | - |
| 1.9410 | 10600 | 0.0015 | - |
| 1.9502 | 10650 | 0.0014 | - |
| 1.9593 | 10700 | 0.0013 | - |
| 1.9685 | 10750 | 0.0032 | - |
| 1.9777 | 10800 | 0.0017 | - |
| 1.9868 | 10850 | 0.0015 | - |
| 1.9960 | 10900 | 0.0012 | - |
| 2.0 | 10922 | - | 0.1071 |
| 2.0051 | 10950 | 0.0013 | - |
| 2.0143 | 11000 | 0.0013 | - |
| 2.0234 | 11050 | 0.0015 | - |
| 2.0326 | 11100 | 0.0013 | - |
| 2.0418 | 11150 | 0.0013 | - |
| 2.0509 | 11200 | 0.0011 | - |
| 2.0601 | 11250 | 0.0013 | - |
| 2.0692 | 11300 | 0.0013 | - |
| 2.0784 | 11350 | 0.0034 | - |
| 2.0875 | 11400 | 0.0012 | - |
| 2.0967 | 11450 | 0.0012 | - |
| 2.1058 | 11500 | 0.0025 | - |
| 2.1150 | 11550 | 0.0026 | - |
| 2.1242 | 11600 | 0.0031 | - |
| 2.1333 | 11650 | 0.0012 | - |
| 2.1425 | 11700 | 0.0011 | - |
| 2.1516 | 11750 | 0.0013 | - |
| 2.1608 | 11800 | 0.0012 | - |
| 2.1699 | 11850 | 0.0013 | - |
| 2.1791 | 11900 | 0.0011 | - |
| 2.1882 | 11950 | 0.0011 | - |
| 2.1974 | 12000 | 0.0012 | - |
| 2.2066 | 12050 | 0.0014 | - |
| 2.2157 | 12100 | 0.003 | - |
| 2.2249 | 12150 | 0.001 | - |
| 2.2340 | 12200 | 0.0011 | - |
| 2.2432 | 12250 | 0.0028 | - |
| 2.2523 | 12300 | 0.0027 | - |
| 2.2615 | 12350 | 0.0013 | - |
| 2.2706 | 12400 | 0.0024 | - |
| 2.2798 | 12450 | 0.0011 | - |
| 2.2890 | 12500 | 0.001 | - |
| 2.2981 | 12550 | 0.0011 | - |
| 2.3073 | 12600 | 0.0011 | - |
| 2.3164 | 12650 | 0.0029 | - |
| 2.3256 | 12700 | 0.0029 | - |
| 2.3347 | 12750 | 0.0009 | - |
| 2.3439 | 12800 | 0.0013 | - |
| 2.3530 | 12850 | 0.0009 | - |
| 2.3622 | 12900 | 0.001 | - |
| 2.3714 | 12950 | 0.0011 | - |
| 2.3805 | 13000 | 0.0027 | - |
| 2.3897 | 13050 | 0.0009 | - |
| 2.3988 | 13100 | 0.0011 | - |
| 2.4080 | 13150 | 0.0012 | - |
| 2.4171 | 13200 | 0.0024 | - |
| 2.4263 | 13250 | 0.0039 | - |
| 2.4355 | 13300 | 0.001 | - |
| 2.4446 | 13350 | 0.0017 | - |
| 2.4538 | 13400 | 0.0012 | - |
| 2.4629 | 13450 | 0.0021 | - |
| 2.4721 | 13500 | 0.0021 | - |
| 2.4812 | 13550 | 0.0032 | - |
| 2.4904 | 13600 | 0.0012 | - |
| 2.4995 | 13650 | 0.0012 | - |
| 2.5087 | 13700 | 0.0014 | - |
| 2.5179 | 13750 | 0.001 | - |
| 2.5270 | 13800 | 0.0011 | - |
| 2.5362 | 13850 | 0.0009 | - |
| 2.5453 | 13900 | 0.0034 | - |
| 2.5545 | 13950 | 0.0015 | - |
| 2.5636 | 14000 | 0.0013 | - |
| 2.5728 | 14050 | 0.0069 | - |
| 2.5819 | 14100 | 0.001 | - |
| 2.5911 | 14150 | 0.0034 | - |
| 2.6003 | 14200 | 0.0028 | - |
| 2.6094 | 14250 | 0.001 | - |
| 2.6186 | 14300 | 0.0012 | - |
| 2.6277 | 14350 | 0.0013 | - |
| 2.6369 | 14400 | 0.0011 | - |
| 2.6460 | 14450 | 0.0009 | - |
| 2.6552 | 14500 | 0.001 | - |
| 2.6643 | 14550 | 0.0009 | - |
| 2.6735 | 14600 | 0.0012 | - |
| 2.6827 | 14650 | 0.0041 | - |
| 2.6918 | 14700 | 0.0008 | - |
| 2.7010 | 14750 | 0.0019 | - |
| 2.7101 | 14800 | 0.001 | - |
| 2.7193 | 14850 | 0.0012 | - |
| 2.7284 | 14900 | 0.0013 | - |
| 2.7376 | 14950 | 0.0012 | - |
| 2.7467 | 15000 | 0.0019 | - |
| 2.7559 | 15050 | 0.0009 | - |
| 2.7651 | 15100 | 0.0009 | - |
| 2.7742 | 15150 | 0.0008 | - |
| 2.7834 | 15200 | 0.0028 | - |
| 2.7925 | 15250 | 0.0009 | - |
| 2.8017 | 15300 | 0.0011 | - |
| 2.8108 | 15350 | 0.0029 | - |
| 2.8200 | 15400 | 0.0008 | - |
| 2.8292 | 15450 | 0.001 | - |
| 2.8383 | 15500 | 0.0019 | - |
| 2.8475 | 15550 | 0.0011 | - |
| 2.8566 | 15600 | 0.0022 | - |
| 2.8658 | 15650 | 0.0011 | - |
| 2.8749 | 15700 | 0.0009 | - |
| 2.8841 | 15750 | 0.0008 | - |
| 2.8932 | 15800 | 0.0009 | - |
| 2.9024 | 15850 | 0.0009 | - |
| 2.9116 | 15900 | 0.0011 | - |
| 2.9207 | 15950 | 0.0011 | - |
| 2.9299 | 16000 | 0.0017 | - |
| 2.9390 | 16050 | 0.001 | - |
| 2.9482 | 16100 | 0.0008 | - |
| 2.9573 | 16150 | 0.0009 | - |
| 2.9665 | 16200 | 0.0008 | - |
| 2.9756 | 16250 | 0.0009 | - |
| 2.9848 | 16300 | 0.0007 | - |
| 2.9940 | 16350 | 0.0011 | - |
| 3.0 | 16383 | - | 0.0990 |
| 3.0031 | 16400 | 0.0008 | - |
| 3.0123 | 16450 | 0.0008 | - |
| 3.0214 | 16500 | 0.0008 | - |
| 3.0306 | 16550 | 0.0008 | - |
| 3.0397 | 16600 | 0.0015 | - |
| 3.0489 | 16650 | 0.0007 | - |
| 3.0580 | 16700 | 0.0008 | - |
| 3.0672 | 16750 | 0.0009 | - |
| 3.0764 | 16800 | 0.0008 | - |
| 3.0855 | 16850 | 0.0008 | - |
| 3.0947 | 16900 | 0.0023 | - |
| 3.1038 | 16950 | 0.0007 | - |
| 3.1130 | 17000 | 0.0006 | - |
| 3.1221 | 17050 | 0.0024 | - |
| 3.1313 | 17100 | 0.0008 | - |
| 3.1405 | 17150 | 0.0017 | - |
| 3.1496 | 17200 | 0.0011 | - |
| 3.1588 | 17250 | 0.0008 | - |
| 3.1679 | 17300 | 0.0008 | - |
| 3.1771 | 17350 | 0.0007 | - |
| 3.1862 | 17400 | 0.0014 | - |
| 3.1954 | 17450 | 0.0008 | - |
| 3.2045 | 17500 | 0.0007 | - |
| 3.2137 | 17550 | 0.0007 | - |
| 3.2229 | 17600 | 0.0006 | - |
| 3.2320 | 17650 | 0.0007 | - |
| 3.2412 | 17700 | 0.0021 | - |
| 3.2503 | 17750 | 0.0006 | - |
| 3.2595 | 17800 | 0.0006 | - |
| 3.2686 | 17850 | 0.0007 | - |
| 3.2778 | 17900 | 0.0006 | - |
| 3.2869 | 17950 | 0.0008 | - |
| 3.2961 | 18000 | 0.0008 | - |
| 3.3053 | 18050 | 0.0008 | - |
| 3.3144 | 18100 | 0.0027 | - |
| 3.3236 | 18150 | 0.0008 | - |
| 3.3327 | 18200 | 0.0007 | - |
| 3.3419 | 18250 | 0.0007 | - |
| 3.3510 | 18300 | 0.0008 | - |
| 3.3602 | 18350 | 0.0007 | - |
| 3.3693 | 18400 | 0.0022 | - |
| 3.3785 | 18450 | 0.0007 | - |
| 3.3877 | 18500 | 0.0014 | - |
| 3.3968 | 18550 | 0.0006 | - |
| 3.4060 | 18600 | 0.0016 | - |
| 3.4151 | 18650 | 0.0007 | - |
| 3.4243 | 18700 | 0.0015 | - |
| 3.4334 | 18750 | 0.0006 | - |
| 3.4426 | 18800 | 0.001 | - |
| 3.4517 | 18850 | 0.0008 | - |
| 3.4609 | 18900 | 0.0008 | - |
| 3.4701 | 18950 | 0.0007 | - |
| 3.4792 | 19000 | 0.0015 | - |
| 3.4884 | 19050 | 0.0007 | - |
| 3.4975 | 19100 | 0.0006 | - |
| 3.5067 | 19150 | 0.0007 | - |
| 3.5158 | 19200 | 0.0014 | - |
| 3.5250 | 19250 | 0.0006 | - |
| 3.5342 | 19300 | 0.0011 | - |
| 3.5433 | 19350 | 0.0008 | - |
| 3.5525 | 19400 | 0.0007 | - |
| 3.5616 | 19450 | 0.0008 | - |
| 3.5708 | 19500 | 0.0021 | - |
| 3.5799 | 19550 | 0.0007 | - |
| 3.5891 | 19600 | 0.0007 | - |
| 3.5982 | 19650 | 0.0006 | - |
| 3.6074 | 19700 | 0.0007 | - |
| 3.6166 | 19750 | 0.0007 | - |
| 3.6257 | 19800 | 0.0007 | - |
| 3.6349 | 19850 | 0.001 | - |
| 3.6440 | 19900 | 0.0011 | - |
| 3.6532 | 19950 | 0.0007 | - |
| 3.6623 | 20000 | 0.0006 | - |
| 3.6715 | 20050 | 0.0022 | - |
| 3.6806 | 20100 | 0.0011 | - |
| 3.6898 | 20150 | 0.0007 | - |
| 3.6990 | 20200 | 0.0006 | - |
| 3.7081 | 20250 | 0.0007 | - |
| 3.7173 | 20300 | 0.0006 | - |
| 3.7264 | 20350 | 0.0006 | - |
| 3.7356 | 20400 | 0.0013 | - |
| 3.7447 | 20450 | 0.0009 | - |
| 3.7539 | 20500 | 0.0006 | - |
| 3.7630 | 20550 | 0.001 | - |
| 3.7722 | 20600 | 0.0007 | - |
| 3.7814 | 20650 | 0.0007 | - |
| 3.7905 | 20700 | 0.0006 | - |
| 3.7997 | 20750 | 0.0006 | - |
| 3.8088 | 20800 | 0.0015 | - |
| 3.8180 | 20850 | 0.0009 | - |
| 3.8271 | 20900 | 0.0009 | - |
| 3.8363 | 20950 | 0.0005 | - |
| 3.8454 | 21000 | 0.0008 | - |
| 3.8546 | 21050 | 0.0006 | - |
| 3.8638 | 21100 | 0.0008 | - |
| 3.8729 | 21150 | 0.0006 | - |
| 3.8821 | 21200 | 0.0006 | - |
| 3.8912 | 21250 | 0.0005 | - |
| 3.9004 | 21300 | 0.0006 | - |
| 3.9095 | 21350 | 0.0015 | - |
| 3.9187 | 21400 | 0.0017 | - |
| 3.9279 | 21450 | 0.0006 | - |
| 3.9370 | 21500 | 0.0007 | - |
| 3.9462 | 21550 | 0.0014 | - |
| 3.9553 | 21600 | 0.0012 | - |
| 3.9645 | 21650 | 0.0017 | - |
| 3.9736 | 21700 | 0.0008 | - |
| 3.9828 | 21750 | 0.0006 | - |
| 3.9919 | 21800 | 0.0006 | - |
| 4.0 | 21844 | - | 0.1004 |
### 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
```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}
}
```
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