--- library_name: setfit tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer metrics: - accuracy widget: - text: 'Walter-Erich Schneider (15 February 1909 – 25 October 1987) was a Kapitänleutnant with the Kriegsmarine during World War II and a recipient of the Knight''s Cross of the Iron Cross (German: Ritterkreuz des Eisernen Kreuzes). The Knight''s Cross of the Iron Cross was awarded to recognise extreme battlefield bravery or successful military leadership.' - text: 'Allen Walker (Japanese: アレン・ウォーカー Hepburn: Aren Wōkā) is a fictional character who appears as the protagonist of the manga D.Gray-man by Katsura Hoshino. He is also the protagonist of its two anime adaptations, D.Gray-man and its sequel D.Gray-man Hallow, and has appeared in three light novels, two video games, and several crossover fighting games.' - text: Riverdale Township is one of twenty-six townships in Buffalo County, Nebraska, United States. The population was 1,939 at the 2000 census. - text: UGC 4879, which is also known as VV 124, is the most isolated dwarf galaxy in the periphery of the Local Group. It is an irregular galaxy at a distance of 1.38 Mpc. - text: 3ZB was a radio station based in Christchurch, New Zealand. This station was run by Radio New Zealand (formally the NZBS/NZBC/BCNZ) and eventually spawned a second FM station called B98FM. pipeline_tag: text-classification inference: true base_model: sentence-transformers/all-MiniLM-L6-v2 model-index: - name: SetFit with sentence-transformers/all-MiniLM-L6-v2 results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 0.8757990867579909 name: Accuracy --- # SetFit with sentence-transformers/all-MiniLM-L6-v2 This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-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/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - **Maximum Sequence Length:** 256 tokens - **Number of Classes:** 219 classes ### 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 | |:-------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | AgentSportsLeagueIceHockeyLeague | | | UnitOfWorkLegalCaseSupremeCourtOfTheUnitedStatesCase | | | AgentSportsTeamHockeyTeam | | | AgentGridironFootballPlayerAmericanFootballPlayer | | | SpeciesAnimalReptile | | | EventSportsEventGrandPrix | | | PlaceVenueTheatre | | | AgentCompanyRecordLabel | | | AgentSportsLeagueBasketballLeague | | | PlaceBuildingPrison | | | AgentBoxerAmateurBoxer | | | WorkMusicalWorkSingle | | | AgentOrganisationPoliticalParty | | | AgentPersonJournalist | | | WorkWrittenWorkPoem | | | PlaceBuildingMuseum | | | SpeciesPlantGreenAlga | | | AgentAthleteSoccerPlayer | | | AgentSportsTeamRugbyClub | | | WorkMusicalWorkClassicalMusicComposition | | | AgentAthleteSquashPlayer | | | WorkCartoonHollywoodCartoon | | | AgentSportsTeamCanadianFootballTeam | | | PlaceSportFacilityCricketGround | | | AgentCompanyBusCompany | | | SpeciesEukaryoteFungus | | | PlaceNaturalPlaceMountainRange | | | AgentClericCardinal | | | SpeciesAnimalFish | | | WorkSongEurovisionSongContestEntry | | | AgentWinterSportPlayerFigureSkater | | | PlaceInfrastructureDam | | | AgentAthleteDartsPlayer | | | PlaceBuildingHospital | | | SportsSeasonFootballLeagueSeasonNationalFootballLeagueSeason | | | WorkComicComicStrip | | | AgentAthleteGaelicGamesPlayer | | | AgentPoliticianCongressman | | | AgentBroadcasterTelevisionStation | | | WorkMusicalWorkAlbum | | | AgentAthleteChessPlayer | | | EventTournamentWomensTennisAssociationTournament | | | WorkPeriodicalLiteratureNewspaper | | | AgentSportsTeamAustralianFootballTeam | | | EventRaceCyclingRace | | | AgentPersonJudge | | | AgentAthleteRugbyPlayer | | | AgentSportsTeamBasketballTeam | | | AgentComicsCharacterAnimangaCharacter | | | AgentSportsLeagueSoccerLeague | | | AgentOrganisationLegislature | | | PlaceSettlementVillage | | | EventSocietalEventMusicFestival | | | PlaceBuildingRestaurant | | | AgentGroupBand | | | EventSocietalEventElection | | | PlaceNaturalPlaceGlacier | | | EventSportsEventWrestlingEvent | | | AgentCompanyWinery | | | SpeciesHorseRaceHorse | | | AgentPersonPhilosopher | | | AgentAthleteBasketballPlayer | | | AgentVolleyballPlayerBeachVolleyballPlayer | | | AgentAthleteBodybuilder | | | SpeciesFloweringPlantGrape | | | AgentOrganisationMemberSportsTeamMember | | | AgentPersonPlayboyPlaymate | | | SpeciesPlantConifer | | | SpeciesPlantCultivatedVariety | | | AgentArtistComedian | | | AgentWinterSportPlayerSkater | | | AgentAthleteTennisPlayer | | | AgentAthletePokerPlayer | | | AgentPersonNoble | | | EventNaturalEventSolarEclipse | | | AgentClericSaint | | | AgentPersonAstronaut | | | PlaceCelestialBodyPlanet | | | AgentWinterSportPlayerCurler | | | AgentScientistMedician | | | AgentCompanyPublisher | | | AgentAthleteAustralianRulesFootballPlayer | | | SpeciesPlantFern | | | AgentBritishRoyaltyBaronet | | | AgentAthleteNetballPlayer | | | AgentBroadcasterBroadcastNetwork | | | WorkPeriodicalLiteratureAcademicJournal | | | AgentPoliticianMemberOfParliament | | | AgentWinterSportPlayerIceHockeyPlayer | | | AgentPresenterRadioHost | | | EventTournamentGolfTournament | | | WorkComicManga | | | EventTournamentTennisTournament | | | AgentAthleteGymnast | | | AgentAthleteBaseballPlayer | | | AgentArtistFashionDesigner | | | AgentAthleteGolfPlayer | | | AgentAthleteJockey | | | AgentAthleteHorseRider | | | AgentOrganisationTradeUnion | | | AgentClericChristianBishop | | | EventRaceHorseRace | | | PlaceRouteOfTransportationRailwayLine | | | AgentArtistPainter | | | AgentAthleteLacrossePlayer | | | AgentFictionalCharacterSoapCharacter | | | EventSocietalEventConvention | | | AgentPoliticianGovernor | | | AgentMotorcycleRiderSpeedwayRider | | | AgentAthleteCanoeist | | | AgentActorVoiceActor | | | PlaceBuildingCastle | | | WorkCartoonAnime | | | AgentWinterSportPlayerSkier | | | AgentWriterHistorian | | | PlaceNaturalPlaceVolcano | | | AgentPersonHorseTrainer | | | AgentPoliticianMayor | | | PlaceSettlementTown | | | WorkMusicalWorkMusical | | | DeviceEngineAutomobileEngine | | | AgentCompanyBank | | | AgentAthleteCricketer | | | AgentSportsLeagueBaseballLeague | | | AgentArtistComicsCreator | | | AgentScientistEntomologist | | | AgentCoachCollegeCoach | | | AgentPersonReligious | | | PlaceAmusementParkAttractionRollerCoaster | | | AgentAthleteCyclist | | | AgentAthleteRower | | | PlaceClericalAdministrativeRegionDiocese | | | EventSocietalEventFilmFestival | | | EventNaturalEventEarthquake | | | PlaceStreamCanal | | | AgentCompanyLawFirm | | | AgentActorAdultActor | | | SportsSeasonSportsTeamSeasonBaseballSeason | | | PlaceBuildingShoppingMall | | | PlaceSportFacilityGolfCourse | | | AgentPersonEconomist | | | AgentPersonBusinessPerson | | | AgentPersonMonarch | | | WorkPeriodicalLiteratureMagazine | | | AgentMusicalArtistClassicalMusicArtist | | | AgentPersonMilitaryPerson | | | SpeciesPlantCycad | | | AgentPersonChef | | | PlaceBuildingHotel | | | SportsSeasonSportsTeamSeasonNCAATeamSeason | | | SportsSeasonSportsTeamSeasonSoccerClubSeason | | | SpeciesPlantMoss | | | AgentArtistPhotographer | | | SpeciesAnimalBird | | | AgentSportsLeagueRugbyLeague | | | AgentCompanyAirline | | | AgentEducationalInstitutionSchool | | | AgentSportsTeamCyclingTeam | | | PlaceRaceTrackRacecourse | | | PlaceBodyOfWaterLake | | | SpeciesAnimalInsect | | | TopicalConceptGenreMusicGenre | | | AgentCompanyBrewery | | | AgentSportsManagerSoccerManager | | | AgentPoliticianPrimeMinister | | | PlaceStreamRiver | | | AgentRacingDriverNascarDriver | | | AgentPersonAmbassador | | | EventSocietalEventMilitaryConflict | | | AgentPoliticianPresident | | | AgentPersonBeautyQueen | | | AgentAthleteTableTennisPlayer | | | AgentAthleteHandballPlayer | | | EventSportsEventFootballMatch | | | PlaceRouteOfTransportationRoad | | | AgentSportsTeamCricketTeam | | | PlaceInfrastructureAirport | | | WorkMusicalWorkArtistDiscography | | | PlaceRouteOfTransportationBridge | | | PlaceBuildingHistoricBuilding | | | AgentEducationalInstitutionUniversity | | | PlaceTowerLighthouse | | | WorkDatabaseBiologicalDatabase | | | SpeciesAnimalArachnid | | | PlaceStationRailwayStation | | | AgentAthleteMartialArtist | | | SpeciesAnimalCrustacean | | | AgentWrestlerSumoWrestler | | | PlaceCelestialBodyGalaxy | | | AgentClericPope | | | PlaceSatelliteArtificialSatellite | | | AgentWriterScreenWriter | | | EventTournamentSoccerTournament | | | AgentOrganisationPublicTransitSystem | | | AgentOrganisationMilitaryUnit | | | SpeciesAnimalMollusca | | | AgentPersonModel | | | AgentBroadcasterRadioStation | | | AgentPoliticianSenator | | | AgentEducationalInstitutionLibrary | | | AgentPersonArchitect | | | AgentSportsTeamHandballTeam | | | AgentRacingDriverFormulaOneRacer | | | AgentAthleteSwimmer | | | PlaceRouteOfTransportationRoadTunnel | | | PlaceSportFacilityStadium | | | WorkSoftwareVideoGame | | | AgentAthleteBadmintonPlayer | | | AgentFictionalCharacterMythologicalFigure | | | AgentPersonEngineer | | | SpeciesAnimalAmphibian | | | EventSportsEventMixedMartialArtsEvent | | | WorkWrittenWorkPlay | | | AgentPersonOfficeHolder | | | EventOlympicsOlympicEvent | | | PlaceNaturalPlaceCave | | | PlaceNaturalPlaceMountainPass | | | AgentWriterPoet | | | PlaceNaturalPlaceMountain | | ## Evaluation ### Metrics | Label | Accuracy | |:--------|:---------| | **all** | 0.8758 | ## 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("mcllstr/setfit-mltclss") # Run inference preds = model("Riverdale Township is one of twenty-six townships in Buffalo County, Nebraska, United States. The population was 1,939 at the 2000 census.") ``` ## Training Details ### Training Set Metrics | Training set | Min | Median | Max | |:-------------|:----|:--------|:----| | Word count | 8 | 36.5080 | 74 | | Label | Training Sample Count | |:-------------------------------------------------------------|:----------------------| | AgentActorAdultActor | 4 | | AgentActorVoiceActor | 4 | | AgentArtistComedian | 4 | | AgentArtistComicsCreator | 4 | | AgentArtistFashionDesigner | 4 | | AgentArtistPainter | 4 | | AgentArtistPhotographer | 4 | | AgentAthleteAustralianRulesFootballPlayer | 4 | | AgentAthleteBadmintonPlayer | 4 | | AgentAthleteBaseballPlayer | 4 | | AgentAthleteBasketballPlayer | 4 | | AgentAthleteBodybuilder | 4 | | AgentAthleteCanoeist | 4 | | AgentAthleteChessPlayer | 4 | | AgentAthleteCricketer | 4 | | AgentAthleteCyclist | 4 | | AgentAthleteDartsPlayer | 4 | | AgentAthleteGaelicGamesPlayer | 4 | | AgentAthleteGolfPlayer | 4 | | AgentAthleteGymnast | 4 | | AgentAthleteHandballPlayer | 4 | | AgentAthleteHorseRider | 4 | | AgentAthleteJockey | 4 | | AgentAthleteLacrossePlayer | 4 | | AgentAthleteMartialArtist | 4 | | AgentAthleteNetballPlayer | 4 | | AgentAthletePokerPlayer | 4 | | AgentAthleteRower | 4 | | AgentAthleteRugbyPlayer | 4 | | AgentAthleteSoccerPlayer | 4 | | AgentAthleteSquashPlayer | 4 | | AgentAthleteSwimmer | 4 | | AgentAthleteTableTennisPlayer | 4 | | AgentAthleteTennisPlayer | 4 | | AgentBoxerAmateurBoxer | 4 | | AgentBritishRoyaltyBaronet | 4 | | AgentBroadcasterBroadcastNetwork | 4 | | AgentBroadcasterRadioStation | 4 | | AgentBroadcasterTelevisionStation | 4 | | AgentClericCardinal | 4 | | AgentClericChristianBishop | 4 | | AgentClericPope | 4 | | AgentClericSaint | 4 | | AgentCoachCollegeCoach | 4 | | AgentComicsCharacterAnimangaCharacter | 4 | | AgentCompanyAirline | 4 | | AgentCompanyBank | 4 | | AgentCompanyBrewery | 4 | | AgentCompanyBusCompany | 4 | | AgentCompanyLawFirm | 4 | | AgentCompanyPublisher | 4 | | AgentCompanyRecordLabel | 4 | | AgentCompanyWinery | 4 | | AgentEducationalInstitutionLibrary | 4 | | AgentEducationalInstitutionSchool | 4 | | AgentEducationalInstitutionUniversity | 4 | | AgentFictionalCharacterMythologicalFigure | 4 | | AgentFictionalCharacterSoapCharacter | 4 | | AgentGridironFootballPlayerAmericanFootballPlayer | 4 | | AgentGroupBand | 4 | | AgentMotorcycleRiderSpeedwayRider | 4 | | AgentMusicalArtistClassicalMusicArtist | 4 | | AgentOrganisationLegislature | 4 | | AgentOrganisationMemberSportsTeamMember | 4 | | AgentOrganisationMilitaryUnit | 4 | | AgentOrganisationPoliticalParty | 4 | | AgentOrganisationPublicTransitSystem | 4 | | AgentOrganisationTradeUnion | 4 | | AgentPersonAmbassador | 4 | | AgentPersonArchitect | 4 | | AgentPersonAstronaut | 4 | | AgentPersonBeautyQueen | 4 | | AgentPersonBusinessPerson | 4 | | AgentPersonChef | 4 | | AgentPersonEconomist | 4 | | AgentPersonEngineer | 4 | | AgentPersonHorseTrainer | 4 | | AgentPersonJournalist | 4 | | AgentPersonJudge | 4 | | AgentPersonMilitaryPerson | 4 | | AgentPersonModel | 4 | | AgentPersonMonarch | 4 | | AgentPersonNoble | 4 | | AgentPersonOfficeHolder | 4 | | AgentPersonPhilosopher | 4 | | AgentPersonPlayboyPlaymate | 4 | | AgentPersonReligious | 4 | | AgentPoliticianCongressman | 4 | | AgentPoliticianGovernor | 4 | | AgentPoliticianMayor | 4 | | AgentPoliticianMemberOfParliament | 4 | | AgentPoliticianPresident | 4 | | AgentPoliticianPrimeMinister | 4 | | AgentPoliticianSenator | 4 | | AgentPresenterRadioHost | 4 | | AgentRacingDriverFormulaOneRacer | 4 | | AgentRacingDriverNascarDriver | 4 | | AgentScientistEntomologist | 4 | | AgentScientistMedician | 4 | | AgentSportsLeagueBaseballLeague | 4 | | AgentSportsLeagueBasketballLeague | 4 | | AgentSportsLeagueIceHockeyLeague | 4 | | AgentSportsLeagueRugbyLeague | 4 | | AgentSportsLeagueSoccerLeague | 4 | | AgentSportsManagerSoccerManager | 4 | | AgentSportsTeamAustralianFootballTeam | 4 | | AgentSportsTeamBasketballTeam | 4 | | AgentSportsTeamCanadianFootballTeam | 4 | | AgentSportsTeamCricketTeam | 4 | | AgentSportsTeamCyclingTeam | 4 | | AgentSportsTeamHandballTeam | 4 | | AgentSportsTeamHockeyTeam | 4 | | AgentSportsTeamRugbyClub | 4 | | AgentVolleyballPlayerBeachVolleyballPlayer | 4 | | AgentWinterSportPlayerCurler | 4 | | AgentWinterSportPlayerFigureSkater | 4 | | AgentWinterSportPlayerIceHockeyPlayer | 4 | | AgentWinterSportPlayerSkater | 4 | | AgentWinterSportPlayerSkier | 4 | | AgentWrestlerSumoWrestler | 4 | | AgentWriterHistorian | 4 | | AgentWriterPoet | 4 | | AgentWriterScreenWriter | 4 | | DeviceEngineAutomobileEngine | 4 | | EventNaturalEventEarthquake | 4 | | EventNaturalEventSolarEclipse | 4 | | EventOlympicsOlympicEvent | 4 | | EventRaceCyclingRace | 4 | | EventRaceHorseRace | 4 | | EventSocietalEventConvention | 4 | | EventSocietalEventElection | 4 | | EventSocietalEventFilmFestival | 4 | | EventSocietalEventMilitaryConflict | 4 | | EventSocietalEventMusicFestival | 4 | | EventSportsEventFootballMatch | 4 | | EventSportsEventGrandPrix | 4 | | EventSportsEventMixedMartialArtsEvent | 4 | | EventSportsEventWrestlingEvent | 4 | | EventTournamentGolfTournament | 4 | | EventTournamentSoccerTournament | 4 | | EventTournamentTennisTournament | 4 | | EventTournamentWomensTennisAssociationTournament | 4 | | PlaceAmusementParkAttractionRollerCoaster | 4 | | PlaceBodyOfWaterLake | 4 | | PlaceBuildingCastle | 4 | | PlaceBuildingHistoricBuilding | 4 | | PlaceBuildingHospital | 4 | | PlaceBuildingHotel | 4 | | PlaceBuildingMuseum | 4 | | PlaceBuildingPrison | 4 | | PlaceBuildingRestaurant | 4 | | PlaceBuildingShoppingMall | 4 | | PlaceCelestialBodyGalaxy | 4 | | PlaceCelestialBodyPlanet | 4 | | PlaceClericalAdministrativeRegionDiocese | 4 | | PlaceInfrastructureAirport | 4 | | PlaceInfrastructureDam | 4 | | PlaceNaturalPlaceCave | 4 | | PlaceNaturalPlaceGlacier | 4 | | PlaceNaturalPlaceMountain | 4 | | PlaceNaturalPlaceMountainPass | 4 | | PlaceNaturalPlaceMountainRange | 4 | | PlaceNaturalPlaceVolcano | 4 | | PlaceRaceTrackRacecourse | 4 | | PlaceRouteOfTransportationBridge | 4 | | PlaceRouteOfTransportationRailwayLine | 4 | | PlaceRouteOfTransportationRoad | 4 | | PlaceRouteOfTransportationRoadTunnel | 4 | | PlaceSatelliteArtificialSatellite | 4 | | PlaceSettlementTown | 4 | | PlaceSettlementVillage | 4 | | PlaceSportFacilityCricketGround | 4 | | PlaceSportFacilityGolfCourse | 4 | | PlaceSportFacilityStadium | 4 | | PlaceStationRailwayStation | 4 | | PlaceStreamCanal | 4 | | PlaceStreamRiver | 4 | | PlaceTowerLighthouse | 4 | | PlaceVenueTheatre | 4 | | SpeciesAnimalAmphibian | 4 | | SpeciesAnimalArachnid | 4 | | SpeciesAnimalBird | 4 | | SpeciesAnimalCrustacean | 4 | | SpeciesAnimalFish | 4 | | SpeciesAnimalInsect | 4 | | SpeciesAnimalMollusca | 4 | | SpeciesAnimalReptile | 4 | | SpeciesEukaryoteFungus | 4 | | SpeciesFloweringPlantGrape | 4 | | SpeciesHorseRaceHorse | 4 | | SpeciesPlantConifer | 4 | | SpeciesPlantCultivatedVariety | 4 | | SpeciesPlantCycad | 4 | | SpeciesPlantFern | 4 | | SpeciesPlantGreenAlga | 4 | | SpeciesPlantMoss | 4 | | SportsSeasonFootballLeagueSeasonNationalFootballLeagueSeason | 4 | | SportsSeasonSportsTeamSeasonBaseballSeason | 4 | | SportsSeasonSportsTeamSeasonNCAATeamSeason | 4 | | SportsSeasonSportsTeamSeasonSoccerClubSeason | 4 | | TopicalConceptGenreMusicGenre | 4 | | UnitOfWorkLegalCaseSupremeCourtOfTheUnitedStatesCase | 4 | | WorkCartoonAnime | 4 | | WorkCartoonHollywoodCartoon | 4 | | WorkComicComicStrip | 4 | | WorkComicManga | 4 | | WorkDatabaseBiologicalDatabase | 4 | | WorkMusicalWorkAlbum | 4 | | WorkMusicalWorkArtistDiscography | 4 | | WorkMusicalWorkClassicalMusicComposition | 4 | | WorkMusicalWorkMusical | 4 | | WorkMusicalWorkSingle | 4 | | WorkPeriodicalLiteratureAcademicJournal | 4 | | WorkPeriodicalLiteratureMagazine | 4 | | WorkPeriodicalLiteratureNewspaper | 4 | | WorkSoftwareVideoGame | 4 | | WorkSongEurovisionSongContestEntry | 4 | | WorkWrittenWorkPlay | 4 | | WorkWrittenWorkPoem | 4 | ### Training Hyperparameters - batch_size: (16, 16) - num_epochs: (2, 2) - max_steps: -1 - sampling_strategy: oversampling - num_iterations: 4 - body_learning_rate: (2e-05, 2e-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: False ### Training Results | Epoch | Step | Training Loss | Validation Loss | |:------:|:----:|:-------------:|:---------------:| | 0.0023 | 1 | 0.1213 | - | | 0.1142 | 50 | 0.0963 | - | | 0.2283 | 100 | 0.02 | - | | 0.3425 | 150 | 0.0062 | - | | 0.4566 | 200 | 0.0358 | - | | 0.5708 | 250 | 0.0168 | - | | 0.6849 | 300 | 0.035 | - | | 0.7991 | 350 | 0.0192 | - | | 0.9132 | 400 | 0.0439 | - | | 1.0274 | 450 | 0.0421 | - | | 1.1416 | 500 | 0.0176 | - | | 1.2557 | 550 | 0.0355 | - | | 1.3699 | 600 | 0.0074 | - | | 1.4840 | 650 | 0.0098 | - | | 1.5982 | 700 | 0.0169 | - | | 1.7123 | 750 | 0.008 | - | | 1.8265 | 800 | 0.0093 | - | | 1.9406 | 850 | 0.0071 | - | ### Framework Versions - Python: 3.10.12 - SetFit: 1.0.3 - Sentence Transformers: 2.6.1 - Transformers: 4.40.0.dev0 - PyTorch: 2.2.1+cu121 - Datasets: 2.18.0 - Tokenizers: 0.15.2 ## 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} } ```