Add SetFit model
Browse files- 1_Pooling/config.json +7 -0
- README.md +228 -0
- config.json +24 -0
- config_sentence_transformers.json +7 -0
- config_setfit.json +4 -0
- model.safetensors +3 -0
- model_head.pkl +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +66 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false
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}
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README.md
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---
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library_name: setfit
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tags:
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- setfit
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- sentence-transformers
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- text-classification
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- generated_from_setfit_trainer
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metrics:
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- accuracy
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widget:
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- text: tron miner contract game . yield diamond 50 times earnings '
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- text: infinite yield revolutionizing yield farming experience optimizing platform
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sustainability , capital efficiency safety . recognize def rapid shifting ecosystem
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. dedicated staying cutting edge creating strategies incentive , utilize compose
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latest secure tech . '
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- text: 'hmmcoin community driven def project . hmmcoin open source , decentralized
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, peer peer digital currency uses innovative coin distribution model ( reward
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level schedule ) . coin distribution model : reward level schedule contains 77
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levels . starts level 1 , request equal 1 pmc . one million coins requested level
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. million withdrawn coins amount received coins next level decrease 7 % . every
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level users need perform actions advance next level . level 1 : 1 pmc actions
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required : 1.000.000 actions level 2 : 0.93 pmc actions required : 1.075.268 actions
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etc . users get coin free pay transaction fee . '''
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- text: ' pump dump cryptocurrency trading game lets make real money buying selling
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coins virtual trading market . '''
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- text: platform daily dividend investments , long term contract 3 tier referral commissions
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. running tron blockchain verified smart contract . dividends starting 2.5 % unlimited
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booster contracts 5.5 % shorter periods . '
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pipeline_tag: text-classification
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inference: true
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base_model: sentence-transformers/paraphrase-mpnet-base-v2
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model-index:
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- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: Unknown
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type: unknown
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split: test
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metrics:
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- type: accuracy
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value: 0.5666990448437753
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name: Accuracy
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---
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# SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-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.
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The model has been trained using an efficient few-shot learning technique that involves:
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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2. Training a classification head with features from the fine-tuned Sentence Transformer.
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## Model Details
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### Model Description
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- **Model Type:** SetFit
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- **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
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- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
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- **Maximum Sequence Length:** 512 tokens
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- **Number of Classes:** 9 classes
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Model Sources
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- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
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- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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### Model Labels
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| Label | Examples |
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|:-------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| games | <ul><li>"crypto football strategic live time free play play earn football ( soccer ) game . players play community members rank high order get rewarded $ ball tokens native token ( $ ball ) used house advertising system . ads displayed game accepting payments $ ball token users able buy formations teams app game specific amount $ ball . 50 80 % tokens collected players buys sent burn address . also , $ ball token going native cryptocurrency upcoming nft marketplace '"</li><li>"`` mint fee 1st 10000th nft 1 sol . mint fee 10001st 20000th nft 20000 fleet tokens . mint fee 20001st 30000th nft 30000 fleet tokens . mint fee 90001st 100000th nft 100000 fleet tokens , upper limit mint forever . 80 % chance mint sheep , 20 % chance mint wolf . wolves alpha property ranging 4 8 , value alpha equal chance mint . sheep stated , 10000 fleet tokens generated every day , 70 % claimed . stated wolves share 30 % total daily output fleet tokens according respective alpha values . example , total 8 sheep 2 wolves stated , total 80000 fleet tokens produced every day . sheep get 7000 fleet tokens . 2 wolves share 24000 fleet tokens . one wolf 's alpha 4 , wolf 's alpha 8 , former get 24000x4 ( 4+8 ) 8000 fleet tokens , latter gets 16000 fleet tokens . claim long time , sheep get fleet tokens last three days claiming , wolf get fleet tokens last day , wolf needs claim every day get maximum benefit . acquired fleet tokens traded dex , minted nft traded nft market . ''"</li><li>" hold.earth new app ethereal blockchain . whereby players buy plots virtual earth , creating designs colouring plots plot owners share fee income generated game . platform development shape games developers extend functionality layering game extensions hold earth app framework . hold.earth simplifies process buying using cryptocurrency , entry level users , simplifying process wallets , crypto purchases illustrating key elements blockchain technology . '"</li></ul> |
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| exchanges | <ul><li>"klayswap complete chain instant swap protocol operates chain liquidity pool , liquidity guaranteed automated market making ( amp ) mechanisms . chain swap service allows anyone play act type token cryptocurrency become liquidity provider earn income transaction fee commissions . klayswap , ethereal based tokens ( eth , orc , dai , wbc ) transferred clayton ecosystem via orbit bridge , transparent ibc bridge , built orbit chain , offer yield farming asset pairings previously unconnected decentralized world '"</li><li>"excalibur exchange fandom based dex , built focus sustainability , capital efficiency supporting new projects . sustainability always issue def space , capital follows incentives , incentives need properly configured encourage longevity capital big focus excalibur , via dynamic incentivization long term taking yield generating governance token separated liquidity rewards , amongst others . excalibur also features highly variable swap fees variety mechanisms support new projects fandom . '"</li><li>"`` honeyswap decentralized exchange built dai chain , enables users experience fast secure transactions incredibly low fees . multiple tokens available swap add liquidity . 1hive honeyswap integrated , 0.05 % collected fees exchange used buy honey token deposit common pool , exchange 's volume increases , buy pressure honey increases well responsibility honey holders allocate tokens productive manner dao 's governance . ''"</li></ul> |
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| social | <ul><li>"allows passively earn interest lending assets help liquidity . fast easy way earn money making secure safe investments active . novice used online decentralized trading , , put sale app website , ensuring monthly revenue allowing users purchase token well . novice escaping entire ecology users may participate trading digitally anywhere globe cheap transaction cost almost free , allowing liberating , strategic , low risk , frictionless experience fully decentralized manner using novice . community oriented money rewards holders distributing others . part decision making process , community members also included give sense ownership assets . burn fees , token burning involves permanently removing digital asset circulation reducing supply . '"</li><li>"violet garden better way connect earn . pass go collect 50 vio , every user , every day . unique identity todays social media plagued fake news , online harassment bots . fighting verifying one person , one account . get paid creating content bidding collect 10 % commission bid content creator previous bidder . instant payment utilising power eos , trades , transfers awards instant . voice voice , unfortunately , shut original social media platform abandoned community created , violet garden build stronger one living eos manner . '"</li><li>" would like introduce matic.tube , vod streaming service based polygon blockchain ! currently two movies available see potential project . '"</li></ul> |
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| defi | <ul><li>" unlock nft potential intrinsic value nts finally unlocked used liquidity def operations permissionless strategy nts , rules , choose time rate loans : rules 100 % decentralized def innovation bridge nft world powerful def ecosystem , new era blockchain innovation permissionless anybody list nts without permission . anybody lend ada without ky . '"</li><li>"provide liquidity safe place . farm earn $ wave token . reviewed rugdoc , ky soon plain audit . able stake stablecoins avoid permanent loss stake lp tokens yield farm pools . community plays central role involved project . also referral program . refer earn 2 % purchased token . wave governance token future l2 . '"</li><li>"goldencake def app created ros.finance allow earn cake free ros holder '"</li></ul> |
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| marketplaces | <ul><li>"seem.ninja offers variety services seem . example allows easy boarding seem card payments smart referral system users set prices . soon seem.ninja also allow everyone quickly purchase seem . '"</li><li>"metamarket aggressive finance smart chain ( bsc ) based nft marketplace . powered metareserve team group experienced knowledgeable blockchain developers , nft fanatics , fintech professionals metamarket aims collaborating brands celebrities create virtual real life utilities . designed offer plethora features users , metamarket nft marketplace , launched , reward potential buyers purchasing exclusive nts bsc based marketplace . first , holders shared private metamarket nft collections receive $ power governance tokens , offering chance vote significant events take place metareserve . additionally , receive rewards airdropped $ power periodically . metamarket users get whitelisted nft collections launch aggressive nft marketplace . '"</li><li>"burden powerful platform creators publish , sell , grow business around content web3 . '"</li></ul> |
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| collectibles | <ul><li>"meta elephant nft series nts based mex mascot 4 grade rarities ( n r sr ssr ) total number 10,000. owners stake nts mine assets participate high quality games chains mex work future . first edition meta elephant nft themed space expedition includes cruise maintenance workers , cruise special forces , cruise navigators , cruise pilots . released certain marketplace form mystery box , chance get meta elephant nft different rarities ! '"</li><li>"`` replace crypto addresses name one time registration fee , renewal fees send crypto , need know recipient 's nft domain . send crypto one domain . worrying sending wrong address . nft domain leased . buy domain one time registration fee never worry renewal . domains stored wallet , like cryptocurrency . control . ''"</li><li>"this series 999 explores playful relationship color , shape , line harmony . artwork combination 9 zones ( 3 rows 3 ) . displayed within 9 zones 1 59 possible smaller pieces , put together makes one large artwork . zones programmed way see duplicated pieces within zones , thus making artwork unique one kind . utility offered 9 zone holders . info come . created toronto artist dan1el . '"</li></ul> |
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| gambling | <ul><li>"bulls cows ( also known cows bulls pigs bulls bulls lots ) old code breaking mind paper pencil game two players , predating commercially marketed board game mastermind . game may date back century uses numbers words . played two opponents . '"</li><li>"casino , leading crypto casino thunder core network , 3,000 games world renowned game providers years experiences fully certified . also offers sports book even pp poker users create tournaments play friends . casino casino operated cybergalaxy b.v. , company registered established laws cacao . cybergalaxy b.v. licensed regulated antillephone n.v '"</li><li>"the highest dividends gambling app . need freeze , play get div ! 60 % house edge go dividends pool . currently , run test mode . 7 games available , auto bets limited max bet . find bug , please contact us telegram . start enjoy high div ! '"</li></ul> |
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| other | <ul><li>"seed multichain , community participation token , encouraging participation creation distribution . sesameseed distributes seed daily reward participation delegated governance across blockchain represents . '"</li><li>"`` stackerdaos one stop shop bitcoin days . stackerdao protocol smart contracts operating system modular comparable days stacks . stackerdao , users form anything ranging completely decentralized days automatic proposal functionality subcats multisigs . stackerdaos provides code platform users launch manage dao based stackerdao operating system . stackerdaos , communities manage dao 's treasury , submit proposals , vote . stackerdaos also provides legal tech tools days avail legal benefits meet compliance obligations , legal entity formation , compliance forms filings , tax assistance. ``"</li><li>"name web3 marketing platform allowing users earn tokens , nts , chain chain rewards completing quests . name , aim onboard empower next billion users web3 providing everyone opportunities . name , see today , one step massive pursuit ambitions personal data ownership , data monetization opportunities , web3 accessibility , comparable , chain agnostic , decentralized social identity . since launch , offered 70,000+ verified users opportunity use data earn 220,000+ rewards quests name alone . users , new incredible quests name coolest companies projects . complete quests claim rewards . companies projects , name opportunity run campaigns accurate predictive results . run campaigns based chain chain verified actions . reward users directly data participation . name currently works going multi chain alongside introducing singular , cross chain , comparable web3 identity many exciting features users companies . '"</li></ul> |
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| high-risk | <ul><li>"cross live lottery crc20 token rewards holders automatic mmf reward payments several times day . launched stealthily governed cream community , make win. ! main goal become largest reliable reward jackpot token cross network . '"</li><li>"get 50 % investments daily . '"</li><li>"`` proof easy invest forever ( poet ) world 's first three dimensional crypto currency generates eth holding tokens ! finally , working three level referral system drain contract ! 5 % easyinvestforever dev fees fees token holders multi level sticky referrals 10 % ( rugged ) buys invests . sell fee reduces time 48 % 8 % ( discourages early dumping ) function send external eth donating div ( directly sends eth token holders ) ability enable apps accept if tokens . zero fees transfers , enabling 3rd party trading . ''"</li></ul> |
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## Evaluation
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### Metrics
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| Label | Accuracy |
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|:--------|:---------|
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| **all** | 0.5667 |
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## Uses
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### Direct Use for Inference
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First install the SetFit library:
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```bash
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pip install setfit
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```
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Then you can load this model and run inference.
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```python
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from setfit import SetFitModel
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# Download from the 🤗 Hub
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model = SetFitModel.from_pretrained("dappradar/setfit-model")
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# Run inference
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preds = model("tron miner contract game . yield diamond 50 times earnings '")
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```
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<!--
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### Downstream Use
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*List how someone could finetune this model on their own dataset.*
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-->
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<!--
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### Out-of-Scope Use
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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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-->
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<!--
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## Bias, Risks and Limitations
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*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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-->
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<!--
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### Recommendations
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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-->
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## Training Details
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### Training Set Metrics
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| Training set | Min | Median | Max |
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|:-------------|:----|:--------|:----|
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| Word count | 7 | 65.7639 | 210 |
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| Label | Training Sample Count |
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|:-------------|:----------------------|
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| collectibles | 8 |
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| defi | 8 |
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| exchanges | 8 |
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| gambling | 8 |
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| games | 8 |
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| high-risk | 8 |
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| marketplaces | 8 |
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| other | 8 |
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| social | 8 |
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### Training Hyperparameters
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- batch_size: (8, 8)
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- num_epochs: (1, 1)
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- max_steps: -1
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- sampling_strategy: oversampling
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- num_iterations: 10
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- body_learning_rate: (2e-05, 1e-05)
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- head_learning_rate: 0.01
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- loss: CosineSimilarityLoss
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- distance_metric: cosine_distance
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- margin: 0.25
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- end_to_end: False
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- use_amp: False
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- warmup_proportion: 0.1
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- seed: 42
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- eval_max_steps: -1
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- load_best_model_at_end: True
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### Training Results
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| Epoch | Step | Training Loss | Validation Loss |
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|:-------:|:-------:|:-------------:|:---------------:|
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| 0.0056 | 1 | 0.1857 | - |
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| 0.2778 | 50 | 0.1235 | - |
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| 0.5556 | 100 | 0.0434 | - |
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| 0.8333 | 150 | 0.0148 | - |
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| **1.0** | **180** | **-** | **0.2355** |
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* The bold row denotes the saved checkpoint.
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### Framework Versions
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- Python: 3.10.12
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- SetFit: 1.0.1
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- Sentence Transformers: 2.2.2
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- Transformers: 4.35.2
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- PyTorch: 2.1.0+cu121
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- Datasets: 2.15.0
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- Tokenizers: 0.15.0
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## Citation
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### BibTeX
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```bibtex
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@article{https://doi.org/10.48550/arxiv.2209.11055,
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doi = {10.48550/ARXIV.2209.11055},
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url = {https://arxiv.org/abs/2209.11055},
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author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
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keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
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title = {Efficient Few-Shot Learning Without Prompts},
|
206 |
+
publisher = {arXiv},
|
207 |
+
year = {2022},
|
208 |
+
copyright = {Creative Commons Attribution 4.0 International}
|
209 |
+
}
|
210 |
+
```
|
211 |
+
|
212 |
+
<!--
|
213 |
+
## Glossary
|
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+
|
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+
*Clearly define terms in order to be accessible across audiences.*
|
216 |
+
-->
|
217 |
+
|
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+
<!--
|
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+
## Model Card Authors
|
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+
|
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+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
222 |
+
-->
|
223 |
+
|
224 |
+
<!--
|
225 |
+
## Model Card Contact
|
226 |
+
|
227 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
228 |
+
-->
|
config.json
ADDED
@@ -0,0 +1,24 @@
|
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+
{
|
2 |
+
"_name_or_path": "checkpoints/step_180/",
|
3 |
+
"architectures": [
|
4 |
+
"MPNetModel"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.1,
|
7 |
+
"bos_token_id": 0,
|
8 |
+
"eos_token_id": 2,
|
9 |
+
"hidden_act": "gelu",
|
10 |
+
"hidden_dropout_prob": 0.1,
|
11 |
+
"hidden_size": 768,
|
12 |
+
"initializer_range": 0.02,
|
13 |
+
"intermediate_size": 3072,
|
14 |
+
"layer_norm_eps": 1e-05,
|
15 |
+
"max_position_embeddings": 514,
|
16 |
+
"model_type": "mpnet",
|
17 |
+
"num_attention_heads": 12,
|
18 |
+
"num_hidden_layers": 12,
|
19 |
+
"pad_token_id": 1,
|
20 |
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"relative_attention_num_buckets": 32,
|
21 |
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"torch_dtype": "float32",
|
22 |
+
"transformers_version": "4.35.2",
|
23 |
+
"vocab_size": 30527
|
24 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,7 @@
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|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "2.0.0",
|
4 |
+
"transformers": "4.7.0",
|
5 |
+
"pytorch": "1.9.0+cu102"
|
6 |
+
}
|
7 |
+
}
|
config_setfit.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"labels": null,
|
3 |
+
"normalize_embeddings": false
|
4 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:424eae6fa27563f9dcc75b4d01e9f0c6ddfb0a701b14a683212508ce55009176
|
3 |
+
size 437967672
|
model_head.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a775f40df49a93648e20bee14b57a9bdca499c72756942d97962ec0a5ff72d5c
|
3 |
+
size 56623
|
modules.json
ADDED
@@ -0,0 +1,14 @@
|
|
|
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|
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|
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|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"idx": 0,
|
4 |
+
"name": "0",
|
5 |
+
"path": "",
|
6 |
+
"type": "sentence_transformers.models.Transformer"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"idx": 1,
|
10 |
+
"name": "1",
|
11 |
+
"path": "1_Pooling",
|
12 |
+
"type": "sentence_transformers.models.Pooling"
|
13 |
+
}
|
14 |
+
]
|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"max_seq_length": 512,
|
3 |
+
"do_lower_case": false
|
4 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,51 @@
|
|
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|
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|
1 |
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{
|
2 |
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"bos_token": {
|
3 |
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|
4 |
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|
5 |
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|
6 |
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|
7 |
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"single_word": false
|
8 |
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},
|
9 |
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"cls_token": {
|
10 |
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"content": "<s>",
|
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|
12 |
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|
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|
14 |
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|
15 |
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|
16 |
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|
17 |
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|
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|
19 |
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|
20 |
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|
21 |
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"single_word": false
|
22 |
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},
|
23 |
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"mask_token": {
|
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"content": "<mask>",
|
25 |
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"lstrip": true,
|
26 |
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|
27 |
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"rstrip": false,
|
28 |
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"single_word": false
|
29 |
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},
|
30 |
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"pad_token": {
|
31 |
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"content": "<pad>",
|
32 |
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"lstrip": false,
|
33 |
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"normalized": false,
|
34 |
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|
35 |
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"single_word": false
|
36 |
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},
|
37 |
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"sep_token": {
|
38 |
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|
39 |
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"lstrip": false,
|
40 |
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|
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"rstrip": false,
|
42 |
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"single_word": false
|
43 |
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},
|
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"unk_token": {
|
45 |
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|
46 |
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|
47 |
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|
48 |
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"rstrip": false,
|
49 |
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"single_word": false
|
50 |
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}
|
51 |
+
}
|
tokenizer.json
ADDED
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|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,66 @@
|
|
|
|
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|
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|
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|
3 |
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|
4 |
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|
5 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
18 |
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},
|
19 |
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"2": {
|
20 |
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|
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|
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|
23 |
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|
24 |
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"single_word": false,
|
25 |
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"special": true
|
26 |
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},
|
27 |
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"104": {
|
28 |
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|
29 |
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|
30 |
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|
31 |
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"rstrip": false,
|
32 |
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|
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"special": true
|
34 |
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},
|
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|
36 |
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|
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|
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|
39 |
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|
40 |
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"single_word": false,
|
41 |
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"special": true
|
42 |
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}
|
43 |
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},
|
44 |
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"bos_token": "<s>",
|
45 |
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"clean_up_tokenization_spaces": true,
|
46 |
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"cls_token": "<s>",
|
47 |
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"do_basic_tokenize": true,
|
48 |
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"do_lower_case": true,
|
49 |
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"eos_token": "</s>",
|
50 |
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"mask_token": "<mask>",
|
51 |
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"max_length": 512,
|
52 |
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"model_max_length": 512,
|
53 |
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|
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|
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|
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|
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|
58 |
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"sep_token": "</s>",
|
59 |
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"stride": 0,
|
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"strip_accents": null,
|
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"tokenize_chinese_chars": true,
|
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"tokenizer_class": "MPNetTokenizer",
|
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"truncation_side": "right",
|
64 |
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"truncation_strategy": "longest_first",
|
65 |
+
"unk_token": "[UNK]"
|
66 |
+
}
|
vocab.txt
ADDED
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See raw diff
|
|