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crypto_individual_infer_model_setfit

Text Classification
setfit
PyTorch
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results
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crypto_individual_infer_model_setfit / README.md
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---
library_name: setfit
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
metrics:
- accuracy
widget:
- text: 'Building TopazMarket Prev AptosLabs Founder AptosNames All views posts
and opinions shared are my own Not financial advice '
- text: 'Founder FrequenC__ an awardwinning marketing agency for the next internet
Mentor speaker cat mom Tweets are my own opinion libertylabsxyz '
- text: No1 ExchangeIndonesia Pertama Terdaftar dan Teregulasi di Bappebti CS Live
Chat 247 Jakarta Capital Region
- text: producer business and elsewhere on leave views my own la gran manzana
- text: Founder GainForestNow CoLead ETHBiodivX CL ClimateChangeAI PhD ETH prevGermanyHong_Kong_SAR_ChinaVietnam
Son of Hoa refugees hehim Zurich Switzerland
pipeline_tag: text-classification
inference: true
base_model: BAAI/bge-small-en-v1.5
model-index:
- name: SetFit with BAAI/bge-small-en-v1.5
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: Unknown
type: unknown
split: test
metrics:
- type: accuracy
value: 0.5565092989985694
name: Accuracy
---
# SetFit with BAAI/bge-small-en-v1.5
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) 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:** [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5)
- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
- **Maximum Sequence Length:** 512 tokens
- **Number of Classes:** 28 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 |
|:---------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| UNDETERMINED | <ul><li>'Professor Emeritus of Cognitive Sciences at the University of California Irvine Research Visual perception evolutionary psychology consciousness AI Irvine CA'</li><li>'Emeritus Professor of War Studies Kings College London just published Command The Politics of Military Operations from Korea to Ukraine UK Penguin US OUP '</li><li>'XML apologist Erlang enthusiast Currently JVMs Performance stuff at Netflix Previously JVMs performative stuff at Twitter Hehim San Francisco California'</li></ul> |
| NFT_ARTIST | <ul><li>'Artist Web3 Marketing Advisor Educator Making history everyday Trapped in the blockchain'</li><li>'OwnYourAssets TokenGatedFile Access For CrossPlatformInteroperableGaming C5isComing CYBΞRVΞRSΞ'</li><li>'Pronounced Akossya artist Zurich'</li></ul> |
| ONCHAIN_ANALYST | <ul><li>'I write about onchain stuff fixer AleoHQ prev rabbithole_gg and plenty of DAOs youve heard of '</li><li>'cofounder 3pochLabs onchain'</li><li>'onchain data farcer building mosaicdrops media CryptoSapiens_ OntologyNetwork OrangeProtocol banklessDAO s0 _buildspace s4 Mosaicverse'</li></ul> |
| BUSINESS_DEVELOPER | <ul><li>'Prev opensea TheBlock__ amazon '</li><li>'Building HxroNetwork variable'</li><li>'Building something old CoFounder alongsidefi '</li></ul> |
| NFT_COLLECTOR | <ul><li>'Building glitchmarfa Collecting brightopps prev brtmoments '</li><li>'My soul is a cat My two children rpcnftclub ChainFeedsxyz Bangkok'</li><li>'prev OpenSea NYC'</li></ul> |
| DEVELOPER | <ul><li>'Architect DoraHacks DoraFactory The everlasting hacker movement Menlo Park'</li><li>'Engineer at Inria scikitlearn developer supported by Python and Machine Learning Between Vannes Paris France'</li><li>'Working paritytech on substrate Views are my own I working mostly with rustlang nowadays '</li></ul> |
| TRADER | <ul><li>'Applied game theorist blog occasionally at formerly not a very serious person Scott Alexander '</li><li>'Crypto Trading Bitcoin class of 2013 insilicotrading COO Banana Cabana'</li><li>'token maxi '</li></ul> |
| COMMUNITY_MANAGER | <ul><li>'chutzpah controlled chaos connoisseur arbitrum chinshilling chinchillin thoughts are my own Rio de Janeiro Brazil'</li><li>'commonsstack CoFounder tecmns Founding Steward KERNEL0x KB5 trustedseed tamaralens '</li><li>'Community Admin at The Arbitrum Foundation Helping to scale Ethereum at Arbitrum Feed KOL Binance WEB3'</li></ul> |
| SECURITY_AUDITOR | <ul><li>'founder adjacentfi cofounder former auditor osec_io MEV on solana '</li><li>'Security Researcher Googles Threat Analysis Group 0days all day Love all things bytes assembly and glitter sheher '</li><li>'採用マーケ得意仮想通貨エンジニア4社1社ホワイトハッカーとして月110万達成現在歯科衛生士の妻と事業開始 実績年商1億超えのマーケ担当 開始5ヶ月で6名見学開始2年で累計DH11名見学6名採用 ハイライト要チェック ブログに今までの有益投稿をまとめました 岩手長野福岡ドバイ沖縄'</li></ul> |
| VENTURE_CAPITALIST | <ul><li>'Liquid Crypto Brevan Howard Prev dragonfly_xyz consensys Arena'</li><li>'maverick LA'</li><li>'Founder of SavvyBooks Degen dcv_capital Summoner ElasticDAO metafam Judge code4rena Contributor CantoPublic Nomadic'</li></ul> |
| INVESTOR | <ul><li>'Crypto Investor at Tephra Digital Ex Head of Research Grayscale DCGco FMR Head of Digital Asset Strategy Fundstrat New York NY'</li><li>'Capital Allocators New York NY'</li><li>'Director of Research Autonomous Technology Robotics ARKinvest Automation robotics energy storage alternative energy and space Disclosure New York NY'</li></ul> |
| ANGEL_INVESTOR | <ul><li>'larp LawliettesLab angel uvocapital '</li><li>'Initiator inverternetwork I Angel Investor I ex Gitcoin '</li><li>'VP Head of BD AleoHQ Mainnet Launch Soon Strategic Advisor VoxiesNFT Angel Investor rcsdao ExOP ExCoinbase Professionally CuriousOpinions My Own Manhattan NY'</li></ul> |
| EXECUTIVE | <ul><li>'Chief Strategy Marketing Officer of Liquidity Group Im also the cofounder of Hudson Rock RockHudsonRock a cybercrime intelligence company TelAviv'</li><li>'CEO Polymarket Ethereum since 14 I love music and collect art new york'</li><li>'CEO StartaleHQ Founder AstarNetwork All things for Web3 for billions Japanese Sota_Web3 Earth'</li></ul> |
| MARKETER | <ul><li>'Director General en Kayum comparador de seguros insurance PPC tech crypto f1 Mexico City Mexico'</li><li>'Insights about Web3 data economy and AI by oceanprotocol Currently in Marcom oceanprotocol ocean Ocean '</li><li>'f加速 ethereum China internet culture history podcast growth marketing realmasknetwork prev newsbreakapp smartnews Zuzalu human Palo Alto USA'</li></ul> |
| DATA_SCIENTIST | <ul><li>'data uniswap prev theTIEIO go bears New York NY'</li><li>'engineering data science a16zcrypto '</li><li>'LangChainAI previously robusthq kensho MLOps Generative AI sports analytics '</li></ul> |
| EDUCATOR | <ul><li>' London'</li><li>'MSc Immunology student Past cofounder prof director USF Center Applied Data Ethics math PhD math_rachelmastodonsocial sheher Brisbane Australia'</li><li>'Here to build shared intelligence listen learn share via community tokenengineering KERNEL0x OptimismGov publicgoods education valuesmatter CyberDyn0x tauranga teikaamaui'</li></ul> |
| INFLUENCER | <ul><li>'the destroyer Titan'</li><li>'Healthy life style healthier bags Cape Town South Africa'</li><li>'Beauty Brains Bitcoin Beauty in an anonymous world'</li></ul> |
| ADVISOR | <ul><li>'A decentralized onchain governance consultant Health Wealth RunItUp The only Alpha discord youll ever need to joingametheoryweb3 squanchland Profit Land'</li><li>'Design director Startup Advisor Midjourney Sharing learnings and prompts In my free time working on offscreenai Vancouver Canada'</li><li>'I help fix and grow crypto portfolios through premium research and strategies 1000 members Founder cshift_io Podcast benandbergs Join 10k Crypto Investors '</li></ul> |
| BLOGGER | <ul><li>'NOW Editor Forbes Writer Stripe HarvardBiz Back on Twitter after ignoring it for a decade I will try my best London'</li><li>'larp coindesk '</li><li>' '</li></ul> |
| RESEARCHER | <ul><li>'Roblox Chief Scientist UWaterloo McGill Prof morgan3dbsky Known for NVIDIA Unity Graphics Codex Markdeep G3D Skylanders E Ink Titan Quest Williams Ontario Canada'</li><li>'Simple human Simple life I am trying to do good around me Empathy creativity inspiration ArigatōMerci For ever apprenti researcher Nulle part ailleurs Nowhere'</li><li>'Research community And we have our own NFT collection Telegram'</li></ul> |
| METAVERSE_ENTHUSIAST | <ul><li>'fluent speaker of http and color virtual world evangelist game developer painter writer cj5 driver San Diego'</li><li>'Blockchain Gaming Evangelist CritTheory Gaming CoFounder Earth'</li><li>'We are a peeple obsessed recruiting service collective Treating everyone like a DMs checked infrequently Metaverse'</li></ul> |
| NODE_OPERATOR | <ul><li>'into protocools and shitposting at nodeguardians '</li><li>' CoFounder of onivalidator Filmmaker People Maxi Los Angeles CA'</li><li>'I attest to block 247 Hobby involves the occasional block proposal Have commercial agreements with the MEV trade association Members of Sync Committees Los Angeles'</li></ul> |
| LAWYER | <ul><li>'Law professor at Cal BerkeleyLaw Berkeley California'</li><li>'IP litigator first sale doctrine respecter schedule a disrespecter wife mom to the tiny boss likes design patents needlework yarn new hampshire'</li><li>'Lawyer FINTConsulting TechPolicy E4EProject upcoming GRC CybersecurityAnalyst ex InstituteGC Tweet law tech policy GRC Cybersecurity Decentralized'</li></ul> |
| DATA_ANALYST | <ul><li>'Llama pilot at and '</li><li>'blockchain data opensea kqian on Dune my views are my own dyor nfa data only wagmi open sea'</li><li>'Blockchain analyst Cat and dog dad Taylor Swift fan Army veteran Pittsburgh PA'</li></ul> |
| MINER | <ul><li>'Blockchain bitcoin mining since 2011 analyst 35 years in IT UnixNetwork engineer fpgachip design exCIO Bitfury BitfuryGroup LNSegWit taproot California USA'</li><li>'Founder and CEO of Austin TX'</li><li>'在币圈捡矿泉水瓶子的人 0xb38544ccf295d78b7ae7b2bae5dbebdb1f09910dcrossbell Member of 33daoweb3 Metaverse'</li></ul> |
| SHITCOINER | <ul><li>'Degen ETH and SOL lover '</li><li>'VMPX mrjacklevin Draculaborg'</li><li>'gripto alt notapornfolder_ '</li></ul> |
| FINANCIAL_ANALYST | <ul><li>'Enrolled Agent Crypto Enthusiast Tax EXPERT StackingSats Chopping Tax Since 2016 NoSatoshiLeftBehind hodlmore payless crypto taxes Longmont CO'</li><li>'Politico financial services editor zwarmbrodtpoliticocom zacharywarmbrodtprotonmailcom Washington DC'</li><li>'Im just lookin for clues at the scene of the crime Sedona Arizona'</li></ul> |
| BUSINESS_ANALYST | <ul><li>'Biz Analyst by day web3crypto learner by nightweekend Optimistic about Crypto FanVajpayeeji NaMo M Andreessen E Musk C Dixon Balaji S web3SF Bay Area'</li></ul> |
## Evaluation
### Metrics
| Label | Accuracy |
|:--------|:---------|
| **all** | 0.5565 |
## 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("kasparas12/crypto_individual_infer_model_setfit")
# Run inference
preds = model("producer business and elsewhere on leave views my own la gran manzana")
```
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### Downstream Use
*List how someone could finetune this model on their own dataset.*
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*List how the model may foreseeably be misused and address what users ought not to do with the model.*
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## 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.*
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## Training Details
### Training Set Metrics
| Training set | Min | Median | Max |
|:-------------|:----|:--------|:----|
| Word count | 1 | 13.3415 | 65 |
| Label | Training Sample Count |
|:---------------------|:----------------------|
| DEVELOPER | 2111 |
| DATA_SCIENTIST | 93 |
| DATA_ANALYST | 25 |
| NODE_OPERATOR | 71 |
| MINER | 47 |
| SECURITY_AUDITOR | 352 |
| INVESTOR | 484 |
| ANGEL_INVESTOR | 160 |
| VENTURE_CAPITALIST | 941 |
| TRADER | 270 |
| SHITCOINER | 88 |
| BUSINESS_DEVELOPER | 917 |
| BUSINESS_ANALYST | 1 |
| COMMUNITY_MANAGER | 401 |
| MARKETER | 190 |
| FINANCIAL_ANALYST | 72 |
| ADVISOR | 150 |
| RESEARCHER | 691 |
| ONCHAIN_ANALYST | 45 |
| EXECUTIVE | 741 |
| INFLUENCER | 834 |
| LAWYER | 137 |
| BLOGGER | 198 |
| NFT_COLLECTOR | 335 |
| NFT_ARTIST | 598 |
| EDUCATOR | 281 |
| METAVERSE_ENTHUSIAST | 132 |
| UNDETERMINED | 2216 |
### Training Hyperparameters
- batch_size: (64, 64)
- num_epochs: (1, 1)
- max_steps: -1
- sampling_strategy: oversampling
- num_iterations: 20
- 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
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
### Training Results
| Epoch | Step | Training Loss | Validation Loss |
|:------:|:----:|:-------------:|:---------------:|
| 0.0001 | 1 | 0.2625 | - |
| 0.0064 | 50 | 0.2677 | - |
| 0.0127 | 100 | 0.2515 | - |
| 0.0191 | 150 | 0.2413 | - |
| 0.0254 | 200 | 0.2374 | - |
| 0.0318 | 250 | 0.2383 | - |
| 0.0381 | 300 | 0.222 | - |
| 0.0445 | 350 | 0.1972 | - |
| 0.0509 | 400 | 0.2268 | - |
| 0.0572 | 450 | 0.2333 | - |
| 0.0636 | 500 | 0.199 | - |
| 0.0699 | 550 | 0.2035 | - |
| 0.0763 | 600 | 0.1676 | - |
| 0.0827 | 650 | 0.1566 | - |
| 0.0890 | 700 | 0.1909 | - |
| 0.0954 | 750 | 0.189 | - |
| 0.1017 | 800 | 0.1872 | - |
| 0.1081 | 850 | 0.1576 | - |
| 0.1144 | 900 | 0.1382 | - |
| 0.1208 | 950 | 0.1603 | - |
| 0.1272 | 1000 | 0.155 | - |
| 0.1335 | 1050 | 0.1764 | - |
| 0.1399 | 1100 | 0.1506 | - |
| 0.1462 | 1150 | 0.1439 | - |
| 0.1526 | 1200 | 0.1581 | - |
| 0.1590 | 1250 | 0.1494 | - |
| 0.1653 | 1300 | 0.1622 | - |
| 0.1717 | 1350 | 0.1503 | - |
| 0.1780 | 1400 | 0.1094 | - |
| 0.1844 | 1450 | 0.1576 | - |
| 0.1907 | 1500 | 0.1194 | - |
| 0.1971 | 1550 | 0.1515 | - |
| 0.2035 | 1600 | 0.1662 | - |
| 0.2098 | 1650 | 0.1642 | - |
| 0.2162 | 1700 | 0.0943 | - |
| 0.2225 | 1750 | 0.1472 | - |
| 0.2289 | 1800 | 0.1622 | - |
| 0.2352 | 1850 | 0.0809 | - |
| 0.2416 | 1900 | 0.1623 | - |
| 0.2480 | 1950 | 0.1444 | - |
| 0.2543 | 2000 | 0.1304 | - |
| 0.2607 | 2050 | 0.1175 | - |
| 0.2670 | 2100 | 0.078 | - |
| 0.2734 | 2150 | 0.1189 | - |
| 0.2798 | 2200 | 0.141 | - |
| 0.2861 | 2250 | 0.1233 | - |
| 0.2925 | 2300 | 0.1446 | - |
| 0.2988 | 2350 | 0.1076 | - |
| 0.3052 | 2400 | 0.1016 | - |
| 0.3115 | 2450 | 0.0818 | - |
| 0.3179 | 2500 | 0.1384 | - |
| 0.3243 | 2550 | 0.1065 | - |
| 0.3306 | 2600 | 0.1029 | - |
| 0.3370 | 2650 | 0.1227 | - |
| 0.3433 | 2700 | 0.0982 | - |
| 0.3497 | 2750 | 0.0959 | - |
| 0.3561 | 2800 | 0.0851 | - |
| 0.3624 | 2850 | 0.1028 | - |
| 0.3688 | 2900 | 0.1136 | - |
| 0.3751 | 2950 | 0.1111 | - |
| 0.3815 | 3000 | 0.115 | - |
| 0.3878 | 3050 | 0.1183 | - |
| 0.3942 | 3100 | 0.0689 | - |
| 0.4006 | 3150 | 0.1004 | - |
| 0.4069 | 3200 | 0.1079 | - |
| 0.4133 | 3250 | 0.112 | - |
| 0.4196 | 3300 | 0.0758 | - |
| 0.4260 | 3350 | 0.09 | - |
| 0.4323 | 3400 | 0.1267 | - |
| 0.4387 | 3450 | 0.1024 | - |
| 0.4451 | 3500 | 0.1352 | - |
| 0.4514 | 3550 | 0.0681 | - |
| 0.4578 | 3600 | 0.0483 | - |
| 0.4641 | 3650 | 0.0937 | - |
| 0.4705 | 3700 | 0.0744 | - |
| 0.4769 | 3750 | 0.0926 | - |
| 0.4832 | 3800 | 0.0764 | - |
| 0.4896 | 3850 | 0.0814 | - |
| 0.4959 | 3900 | 0.108 | - |
| 0.5023 | 3950 | 0.0936 | - |
| 0.5086 | 4000 | 0.0687 | - |
| 0.5150 | 4050 | 0.0607 | - |
| 0.5214 | 4100 | 0.0829 | - |
| 0.5277 | 4150 | 0.0772 | - |
| 0.5341 | 4200 | 0.0309 | - |
| 0.5404 | 4250 | 0.0797 | - |
| 0.5468 | 4300 | 0.063 | - |
| 0.5532 | 4350 | 0.071 | - |
| 0.5595 | 4400 | 0.0667 | - |
| 0.5659 | 4450 | 0.121 | - |
| 0.5722 | 4500 | 0.0565 | - |
| 0.5786 | 4550 | 0.0915 | - |
| 0.5849 | 4600 | 0.0613 | - |
| 0.5913 | 4650 | 0.0479 | - |
| 0.5977 | 4700 | 0.0622 | - |
| 0.6040 | 4750 | 0.0687 | - |
| 0.6104 | 4800 | 0.0635 | - |
| 0.6167 | 4850 | 0.1233 | - |
| 0.6231 | 4900 | 0.0351 | - |
| 0.6295 | 4950 | 0.0717 | - |
| 0.6358 | 5000 | 0.0906 | - |
| 0.6422 | 5050 | 0.0712 | - |
| 0.6485 | 5100 | 0.1133 | - |
| 0.6549 | 5150 | 0.0757 | - |
| 0.6612 | 5200 | 0.0809 | - |
| 0.6676 | 5250 | 0.112 | - |
| 0.6740 | 5300 | 0.0893 | - |
| 0.6803 | 5350 | 0.0591 | - |
| 0.6867 | 5400 | 0.0872 | - |
| 0.6930 | 5450 | 0.0937 | - |
| 0.6994 | 5500 | 0.038 | - |
| 0.7057 | 5550 | 0.0793 | - |
| 0.7121 | 5600 | 0.0569 | - |
| 0.7185 | 5650 | 0.0861 | - |
| 0.7248 | 5700 | 0.1022 | - |
| 0.7312 | 5750 | 0.0759 | - |
| 0.7375 | 5800 | 0.0451 | - |
| 0.7439 | 5850 | 0.08 | - |
| 0.7503 | 5900 | 0.058 | - |
| 0.7566 | 5950 | 0.0423 | - |
| 0.7630 | 6000 | 0.043 | - |
| 0.7693 | 6050 | 0.109 | - |
| 0.7757 | 6100 | 0.072 | - |
| 0.7820 | 6150 | 0.0342 | - |
| 0.7884 | 6200 | 0.0833 | - |
| 0.7948 | 6250 | 0.0643 | - |
| 0.8011 | 6300 | 0.1069 | - |
| 0.8075 | 6350 | 0.0713 | - |
| 0.8138 | 6400 | 0.0807 | - |
| 0.8202 | 6450 | 0.0518 | - |
| 0.8266 | 6500 | 0.0796 | - |
| 0.8329 | 6550 | 0.0954 | - |
| 0.8393 | 6600 | 0.0709 | - |
| 0.8456 | 6650 | 0.0541 | - |
| 0.8520 | 6700 | 0.0503 | - |
| 0.8583 | 6750 | 0.0737 | - |
| 0.8647 | 6800 | 0.0931 | - |
| 0.8711 | 6850 | 0.0636 | - |
| 0.8774 | 6900 | 0.0579 | - |
| 0.8838 | 6950 | 0.1168 | - |
| 0.8901 | 7000 | 0.0751 | - |
| 0.8965 | 7050 | 0.0945 | - |
| 0.9028 | 7100 | 0.0396 | - |
| 0.9092 | 7150 | 0.0623 | - |
| 0.9156 | 7200 | 0.0641 | - |
| 0.9219 | 7250 | 0.0697 | - |
| 0.9283 | 7300 | 0.0675 | - |
| 0.9346 | 7350 | 0.0544 | - |
| 0.9410 | 7400 | 0.0803 | - |
| 0.9474 | 7450 | 0.0549 | - |
| 0.9537 | 7500 | 0.0612 | - |
| 0.9601 | 7550 | 0.0721 | - |
| 0.9664 | 7600 | 0.0692 | - |
| 0.9728 | 7650 | 0.07 | - |
| 0.9791 | 7700 | 0.0476 | - |
| 0.9855 | 7750 | 0.0673 | - |
| 0.9919 | 7800 | 0.0606 | - |
| 0.9982 | 7850 | 0.1001 | - |
### Framework Versions
- Python: 3.9.16
- SetFit: 1.0.3
- Sentence Transformers: 2.2.2
- Transformers: 4.21.3
- PyTorch: 1.12.1+cu116
- Datasets: 2.4.0
- Tokenizers: 0.12.1
## 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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