Upload DistilBertForSequenceClassification

README.md

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+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]

config.json

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+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "unknown",
+    "1": "2theloo",
+    "2": "365 Retail Markets",
+    "3": "A1",
+    "4": "A4 Brescia Padova",
+    "5": "AMZS",
+    "6": "ASFINAG",
+    "7": "ASICS",
+    "8": "ATAC",
+    "9": "ATU",
+    "10": "AWS",
+    "11": "Abacus Cooperativa",
+    "12": "Accounting and Corporate Regulatory Authority",
+    "13": "Advance Auto Parts",
+    "14": "Adyen",
+    "15": "Aelia Duty Free",
+    "16": "Aida",
+    "17": "Air Europa",
+    "18": "Akakiko",
+    "19": "Alamo",
+    "20": "Alcott",
+    "21": "Alipay",
+    "22": "Alldrink",
+    "23": "Allo Pizza",
+    "24": "Al\u00ec Supermercati",
+    "25": "AmRest",
+    "26": "Amazon Kids+",
+    "27": "American Eagle Outfitter",
+    "28": "American Express",
+    "29": "Amorino",
+    "30": "Apollo Kino",
+    "31": "Appart'City",
+    "32": "April",
+    "33": "Arabica Coffee",
+    "34": "Areas",
+    "35": "Arenal",
+    "36": "Atlantsol\u00eda",
+    "37": "Atm.it",
+    "38": "Audi",
+    "39": "AutoZone",
+    "40": "Autopistas",
+    "41": "Aux Delices",
+    "42": "Avianca Airlines",
+    "43": "Avoca",
+    "44": "B+B Parkhaus",
+    "45": "BCC Roma",
+    "46": "BNP Paribas",
+    "47": "BVG",
+    "48": "Backstube W\u00fcnsche",
+    "49": "Badische Backstub",
+    "50": "Bargain Booze",
+    "51": "Basic-Fit",
+    "52": "BayWa",
+    "53": "Bellaflora",
+    "54": "Best-One",
+    "55": "Beyfin",
+    "56": "Bi1",
+    "57": "Bico de Xeado",
+    "58": "BigMat",
+    "59": "Bingo City Center",
+    "60": "Bird",
+    "61": "Blaze Pizza",
+    "62": "Block House",
+    "63": "Blokker",
+    "64": "Bombon Boss",
+    "65": "Bookstation",
+    "66": "Boom Battle Bar",
+    "67": "Boost Juice Bars",
+    "68": "Boulangerie Ange",
+    "69": "Boursorama",
+    "70": "Boux Avenue",
+    "71": "Brandy Melville",
+    "72": "Bricorama",
+    "73": "Bubble",
+    "74": "Buc-ee's",
+    "75": "BudgetAir",
+    "76": "Bund.de",
+    "77": "Bupa",
+    "78": "Bureau Vall\u00e9e",
+    "79": "Burgermeister",
+    "80": "Butlers",
+    "81": "Bwin",
+    "82": "B\u00e4ckerei Bauder",
+    "83": "B\u00e4ckerei Drei\u00dfig",
+    "84": "B\u00e4ckerei Hoefer",
+    "85": "B\u00e4ckerei Terbuyken",
+    "86": "B\u00e4ckerei Werning",
+    "87": "B\u00e4ckermeister Haferkamp",
+    "88": "CAP-Markt",
+    "89": "CBA",
+    "90": "CIBTP",
+    "91": "CVMaker.uk",
+    "92": "Caf De Paris",
+    "93": "Cafe & Bar Celona",
+    "94": "Cafe del Sol",
+    "95": "Caja Rural",
+    "96": "Cake Box",
+    "97": "Calpam",
+    "98": "Calvin Klein",
+    "99": "Canteen",
+    "100": "Careem",
+    "101": "Carhartt",
+    "102": "Caribou Coffee",
+    "103": "Carter's",
+    "104": "Casa del Libro",
+    "105": "Cats Protection",
+    "106": "Centauro Rent a Car",
+    "107": "Center Parcs",
+    "108": "Centrakor",
+    "109": "Certa",
+    "110": "ChargePoint",
+    "111": "Checkers",
+    "112": "Cinemark",
+    "113": "Cineplex",
+    "114": "Cinesa",
+    "115": "Cineworld",
+    "116": "CitizenM",
+    "117": "City Gross",
+    "118": "City Market",
+    "119": "City of Quebec",
+    "120": "Clarks",
+    "121": "Coin.it",
+    "122": "Columbus Cafe",
+    "123": "Conrad",
+    "124": "Copa Airlines",
+    "125": "Coutellerie La Civette",
+    "126": "Credit Engine",
+    "127": "Crunchyroll",
+    "128": "Curzon",
+    "129": "DGFIP",
+    "130": "DPD",
+    "131": "DPMCB",
+    "132": "Daiso",
+    "133": "Day Today",
+    "134": "Dec\u00f2",
+    "135": "DeepL",
+    "136": "Dehner",
+    "137": "Deiters",
+    "138": "Delitraiteur",
+    "139": "Delmart",
+    "140": "Der B\u00e4cker Ruetz",
+    "141": "Der Rundfunkbeitrag",
+    "142": "Deutsche Bank",
+    "143": "Deutsche Post",
+    "144": "Deutsche Rentenversicherung",
+    "145": "Digital River",
+    "146": "Disa",
+    "147": "Dishoom",
+    "148": "Disney+",
+    "149": "Dnata",
+    "150": "Dom Lek\u00f3w",
+    "151": "Dr Martens",
+    "152": "Dussmann",
+    "153": "Dyson",
+    "154": "E.ON",
+    "155": "EE",
+    "156": "EOS",
+    "157": "EasyPark",
+    "158": "Ebl-Naturkost",
+    "159": "Edenred",
+    "160": "Eharmony",
+    "161": "Eko Okna",
+    "162": "El Rinc\u00f3n",
+    "163": "Elior",
+    "164": "Emirates Leisure Retail",
+    "165": "Emmerys",
+    "166": "EnBW",
+    "167": "Enchilada",
+    "168": "Engie",
+    "169": "Enrique Tomas",
+    "170": "Enterprise Rent-A-Car",
+    "171": "Ergo",
+    "172": "EsclatOil",
+    "173": "Etam",
+    "174": "Etsan",
+    "175": "EuroPark",
+    "176": "Everest",
+    "177": "F1 Gas",
+    "178": "FEBO",
+    "179": "FairPrice",
+    "180": "Farmacias Benavides",
+    "181": "Fastweb",
+    "182": "Feu Vert",
+    "183": "Fina",
+    "184": "Firehouse Subs",
+    "185": "Fitinn",
+    "186": "FlixBus",
+    "187": "Flyeralarm",
+    "188": "Footasylum",
+    "189": "Four Seasons",
+    "190": "Frankonia",
+    "191": "Free People",
+    "192": "Freie Tankstelle",
+    "193": "G La Dalle",
+    "194": "GAME",
+    "195": "GNC",
+    "196": "Galaxias",
+    "197": "Galaxus",
+    "198": "Galeries Lafayette",
+    "199": "Gall & Gall",
+    "200": "Gamma",
+    "201": "Gedimat",
+    "202": "Geldmaat",
+    "203": "Generali",
+    "204": "GetYourGuide",
+    "205": "Getgo",
+    "206": "Getr\u00e4nke Hoffmann",
+    "207": "GoDaddy",
+    "208": "Goldcar",
+    "209": "Google Fi",
+    "210": "Greens Supermarket",
+    "211": "Greffe du Tribunal",
+    "212": "Grenke",
+    "213": "Groupon",
+    "214": "Gucci",
+    "215": "Guess",
+    "216": "HD Hotels",
+    "217": "HSBC",
+    "218": "Hamburg Airport",
+    "219": "Hannaford",
+    "220": "Hans im Gl\u00fcck",
+    "221": "Harald Nyborg",
+    "222": "Hebe",
+    "223": "Heinemann",
+    "224": "HelloFresh",
+    "225": "Hermes",
+    "226": "Herm\u00e8s",
+    "227": "Hickey's Pharmacy",
+    "228": "Hilti",
+    "229": "Hilton Garden Inn",
+    "230": "Hilton Garden Inn Hotel",
+    "231": "Hiper Centro",
+    "232": "Holland & Barrett",
+    "233": "Hollister Co.",
+    "234": "Hollywood Bowl",
+    "235": "Honest Greens",
+    "236": "Hostinger",
+    "237": "Hotel Barcel\u00f3",
+    "238": "Hotel Mama Shelter",
+    "239": "Hotel Silken",
+    "240": "Hru\u0161ka",
+    "241": "Hudson",
+    "242": "Hugo Boss",
+    "243": "Humana",
+    "244": "HungryPanda",
+    "245": "Hyper U",
+    "246": "IC Cash Services",
+    "247": "IHK",
+    "248": "IQOS",
+    "249": "ISS World",
+    "250": "Illy",
+    "251": "Ilusiona",
+    "252": "In-N-Out Burger",
+    "253": "Ingram Micro",
+    "254": "Insomnia Coffee",
+    "255": "InterContinental",
+    "256": "Interparking",
+    "257": "Iperal",
+    "258": "Italmark",
+    "259": "JP \"Putevi Srbije\"",
+    "260": "Jack & Jones",
+    "261": "Jacques' Wein-Depot",
+    "262": "Jadrolinija",
+    "263": "Juan Valdez",
+    "264": "Jumeirah",
+    "265": "Jump Juice Bar",
+    "266": "JustAnswer",
+    "267": "K-Rauta",
+    "268": "KKH",
+    "269": "KRAJ",
+    "270": "KTC",
+    "271": "Kastner & \u00d6hler",
+    "272": "Kinepolis",
+    "273": "Klarna",
+    "274": "Kramb\u00fa\u00f0",
+    "275": "Kravag",
+    "276": "Kritikos",
+    "277": "Kwik Trip",
+    "278": "LNER",
+    "279": "LPA",
+    "280": "La Fourn\u00e9e",
+    "281": "La Sirena",
+    "282": "La Vie Claire",
+    "283": "Lacoste",
+    "284": "Lariviere",
+    "285": "Lastminute.com",
+    "286": "Le Burger",
+    "287": "Le Crobag",
+    "288": "Le Five",
+    "289": "Le Paradis du Fruit",
+    "290": "Lebara",
+    "291": "Lefties",
+    "292": "Legoland",
+    "293": "Leon Restaurants",
+    "294": "Les D\u00e9lices",
+    "295": "Levaduramadre",
+    "296": "Lindt",
+    "297": "Lloyds Farmacia",
+    "298": "Loblaws",
+    "299": "Localiza",
+    "300": "Lojas Renner",
+    "301": "Longchamp",
+    "302": "Lotto",
+    "303": "Lovisa",
+    "304": "Lush Cosmetics",
+    "305": "MTA",
+    "306": "MVG",
+    "307": "Macy's",
+    "308": "Maiora",
+    "309": "Maison de la Presse",
+    "310": "Maisons du Monde",
+    "311": "Manchester Airport",
+    "312": "Manufactum",
+    "313": "March\u00e9 Schweiz",
+    "314": "Marco's Pizza",
+    "315": "Marien-Apotheke Krailling",
+    "316": "Markant",
+    "317": "Markant Supermarkt",
+    "318": "Market Basket",
+    "319": "Massimo Dutti",
+    "320": "Medi-Market",
+    "321": "Meijer",
+    "322": "Meininger Hotels",
+    "323": "Mercado Extra",
+    "324": "Mercedes-Benz",
+    "325": "Merkur",
+    "326": "Meu Super",
+    "327": "Micromania",
+    "328": "Minecraft",
+    "329": "Minera",
+    "330": "Miscusi",
+    "331": "Mladinska",
+    "332": "Mon Voisin",
+    "333": "Mondadori Store",
+    "334": "MoneyGram",
+    "335": "Moto Motorway",
+    "336": "Mr. Bricolage",
+    "337": "Mundorf Tank",
+    "338": "M\u00f6belix",
+    "339": "M\u0113ness aptieka",
+    "340": "NOZ",
+    "341": "Nah & Gut",
+    "342": "National Rail",
+    "343": "Nayax",
+    "344": "Netto Denmark",
+    "345": "Netto Marken-Discount",
+    "346": "Newcastle City Council",
+    "347": "Next",
+    "348": "Nordsee",
+    "349": "Norfa",
+    "350": "Notino",
+    "351": "N\u00fcrnberger Versicherung",
+    "352": "O'Reilly Auto Parts",
+    "353": "O'Tacos",
+    "354": "OK Mobility",
+    "355": "OKay",
+    "356": "OVHcloud",
+    "357": "Ochsner Sport",
+    "358": "Old Wild West",
+    "359": "Ole & Steen",
+    "360": "Omio",
+    "361": "Omniva",
+    "362": "Oney",
+    "363": "OnlyFans",
+    "364": "OpenCor Vending",
+    "365": "Osiander",
+    "366": "P.F. Chang's",
+    "367": "POLOmarket",
+    "368": "PRIO",
+    "369": "Pad in Portugal",
+    "370": "Panet",
+    "371": "Panos",
+    "372": "Paracelsus Apotheke",
+    "373": "Parken",
+    "374": "Patagonia",
+    "375": "Peter Pane",
+    "376": "Pho",
+    "377": "Planet Fitness",
+    "378": "PlayStation",
+    "379": "Point Chaud",
+    "380": "Pokawa",
+    "381": "Poke House",
+    "382": "Polonez",
+    "383": "Pomme de Pain",
+    "384": "Post Luxembourg",
+    "385": "Potraviny",
+    "386": "Power.dk",
+    "387": "Proxi",
+    "388": "Proxim Supermercado",
+    "389": "Public Storage",
+    "390": "Putka",
+    "391": "Qonto",
+    "392": "RTA",
+    "393": "Radatz",
+    "394": "Radstock Co-operative",
+    "395": "Ralphs",
+    "396": "Real",
+    "397": "Riachuelo",
+    "398": "Ring",
+    "399": "RingGo",
+    "400": "Roblox",
+    "401": "Rocket Lawyer",
+    "402": "Roku",
+    "403": "Rontec",
+    "404": "Rossopomodoro",
+    "405": "Ruch",
+    "406": "SFR",
+    "407": "STACH",
+    "408": "Samsung",
+    "409": "SandwiChez",
+    "410": "Santagloria",
+    "411": "Saturn",
+    "412": "Second Cup",
+    "413": "Selfridges",
+    "414": "Servei Estaci\u00f3",
+    "415": "Service NSW",
+    "416": "Sigma",
+    "417": "Silvan",
+    "418": "Six",
+    "419": "Slim Chickens",
+    "420": "Smart Parking",
+    "421": "Smarty Cashback",
+    "422": "Smullers",
+    "423": "Snappy Snaps",
+    "424": "Sokos Hotels",
+    "425": "Sonnen Apotheke",
+    "426": "Spar University",
+    "427": "Spearhead Taxis",
+    "428": "Spinneys",
+    "429": "Sportler",
+    "430": "Sp\u00e4tkauf",
+    "431": "Square",
+    "432": "Stadt Wien",
+    "433": "Stadt-Apotheke",
+    "434": "Star Tankstelle",
+    "435": "Stark Deutschland",
+    "436": "Steam",
+    "437": "Stena Line",
+    "438": "Stockmann",
+    "439": "Stripe",
+    "440": "Stroili Oro",
+    "441": "SumUp",
+    "442": "Suma",
+    "443": "Suma Supermercados",
+    "444": "Super Muffato",
+    "445": "Super-Pharm",
+    "446": "SuperFit",
+    "447": "Superbet",
+    "448": "Supermercado Bip Bip",
+    "449": "Swatch",
+    "450": "S\u00f8strene Grene",
+    "451": "T&G",
+    "452": "TGI Friday's",
+    "453": "Tabac Presse",
+    "454": "Taboola",
+    "455": "Tallink",
+    "456": "Tam",
+    "457": "Tank & Rast",
+    "458": "Tank Ono",
+    "459": "Team Autohof",
+    "460": "Teboil",
+    "461": "TeeGschwendner",
+    "462": "Telef\u00f3nica",
+    "463": "Temu",
+    "464": "Tenpin",
+    "465": "Thameslink",
+    "466": "The ASH",
+    "467": "The Alchemist",
+    "468": "The Coffee Bean & Tea Leaf",
+    "469": "The Copenhagen Metro",
+    "470": "The Fresh Market",
+    "471": "The Good Burger",
+    "472": "The North Face",
+    "473": "The Range",
+    "474": "The Social Hub",
+    "475": "The niu",
+    "476": "Thomann",
+    "477": "Three",
+    "478": "Tibits",
+    "479": "TikTok",
+    "480": "Tisak",
+    "481": "Tom Tailor",
+    "482": "Toom",
+    "483": "Top Oil",
+    "484": "Totally Wicked",
+    "485": "Toyota",
+    "486": "Trader Joe's",
+    "487": "TradingView",
+    "488": "Trainline",
+    "489": "TransAct",
+    "490": "Transact.de",
+    "491": "Transdev",
+    "492": "Transgourmet",
+    "493": "Transports Publics Genevois",
+    "494": "Transports Publics Lausannois",
+    "495": "Trenitalia",
+    "496": "Trgovina Krk",
+    "497": "Truffaut",
+    "498": "Turris",
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