SetFit with sentence-transformers/all-mpnet-base-v2

This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/all-mpnet-base-v2 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.

The model has been trained using an efficient few-shot learning technique that involves:

Fine-tuning a Sentence Transformer with contrastive learning.
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-mpnet-base-v2
Classification head: a LogisticRegression instance
Maximum Sequence Length: 384 tokens
Number of Classes: 11 classes

Model Sources

Repository: SetFit on GitHub
Paper: Efficient Few-Shot Learning Without Prompts
Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts

Model Labels

Label	Examples
adult content	'gay men ring free gay tube for mature gay men updated with gay porn videos and gay sex movies' 'seemomsuck packed with the best amateur step mom blowjobs download hot x000d mom and teen blowjob videos seemomsuck' 'xreview com provides depth porn site reviews and offers discount codes and links off some the top porn sites the internet'
suicide	"wife threatening suiciderecently left wife for good because she has cheated twice and lied much that have decided refuse back her. few days ago, she began threatening suicide. have tirelessly spent these paat few days talking her out and she keeps hesitating because she wants believe i'll come back. know lot people will threaten this order get their way, but what happens she really does? what and how supposed handle her death hands? still love wife but cannot deal with getting cheated again and constantly feeling insecure. i'm worried today may the day she does and hope much doesn't happen." 'need helpjust help crying hard' 'i’m losthello, name adam and i’ve been struggling for years and i’m afraid. through these past years thoughts suicide, fear, anxiety i’m close limit i’ve been quiet for long and i’m too scared come out family about these feelings. about years ago losing aunt triggered all. everyday feeling hopeless lost, guilty, and remorseful over her and all the things i’ve done life,but thoughts like these with the little i’ve experienced life? only time i’ve revealed these feelings family when broke down where they saw cuts. watching them get worried over something portrayed average day made feel absolutely dreadful. they later found out was attempt survivor from attempt od(overdose from pills) and attempt hanging. all that happened was blackout from the pills and never went through with the noose because i’m still afraid. during first therapy was diagnosed with severe depression, social anxiety, and eating disorder. was later transferred fucken group therapy for some reason which made feel more anxious. eventually before last session with therapy she showed results from daily check feelings(which was step survey for and mom/dad come find out i’ve been putting feeling horrible and afraid/anxious everyday mom has been doing i’ve been doing absolutely amazing with described “happiest she’s ever seen me, therapy has helped him” eventually was put sertaline (anti anxiety anti depression i’m sorry forgot) but never finished first prescription nor ever found the right type anti depressant because mom thought only wanted the drugs she took off recommended pill schedule after week and stopped from taking them. all this time i’ve been feeling worse afraid the damage/ worry i’ve caused them even more. now here with everything going on, i’m afraid i’ve ever been i’ve relapsed cutting and have developed severe insomnia day after day feeling more hopeless, worthless questioning why still here? what’s motivation move out bed and keep going? ask these myself nearly every night almost having break down everytime. please please please someone.. anyone help me. i’m scared might something drastic, i’ve been shaped fear and anxiety. idk what anymore'
gun violence	'anti-gun student walkout included stomping american flag and jumping cop car' 'parkland students brand firearm ban during pence speech nra hypocrisy' 'oliver north and the nra deserve each other'
discrimination	"we're looking for someone with more aesthetically pleasing face for this role" "we're looking for someone with more appealing body type for this position" "we're looking for someone with more attractive appearance for this role"
sexual harassment	'was walking along crowded street, holding mums hand, when elderly man groped butt, turned look h7m and looked away, and did again after while.i was yrs old then.' 'poor street lighting' "this happened bus, public transport. was broad daylight. was way college and the bus wasn't that crowded. there was enough space for two people stand back back with big bags 'em. this particular male was standing next seat. there was enough and more space behind him. but noooooo... started rubbing his crotch against shoulder, subtly first and then very obviously. made discomfort very apparent. but didn't seem get it. shifted inside seat and did he. think the lady beside knew what was going but didn't say word, neither did the people behind nor the bus conductor. well neither did the first place, was frozen and gripped shock and fear. think now better prepared make shit down someone tries the same feat with me. but i'll never know."
derogatory	'fuck that dont wanna watch tranny porn.' 'opie just wanted have good time. the same old rant about africans from ant and the same old joke about tranny cock from jim. opie admitted and accepted his place the show. was the two other queens who couldnâ€t keep together. opie âœš' 'fuck that faggot fallon. fucking sissy boy acting like year old playing slumber party games. put norm amp louis tour together. see how much fucking money they make together.'
hate	'dalits are lowlives' 'gay people are burden our society' 'arabs are not welcome'
toxic	'cocksucker before you piss around work' 'hey... what it.. talk what it... exclusive group some talibans...who are good destroying, self-appointed purist who gang any one who asks them questions abt their anti-social and destructive (non)-contribution wp? ask sityush clean his behavior than issue nonsensical warnings...' "bye don't look, come think comming back tosser."
physical violence	'husband beats frequently, wife tells court' 'best thing for do, remain silent when return work today. nobody wants hear anything from me, unless husband beats me.' 'husband will never beat me, bambam denies rumour that teddya beats her'
bullying	"here home. neighbors pick family and mind you son autistic. feels like high school. they call names attack for reason and bully all the time. can't step front porch without them doing something" 'being bullied school: high-achieving boys use further strategies maintain masculinity, for example becoming bullies themselves, disrupting the lessons, devaluing girls’ achievements https://www.bipartisanalliance.com///being-bullied-at-school-high-achieving.html?spref=tw' 'there was girl class 6th grade who was little autistic, and her parents thought it’d better send her public school. she didn’t fit with the class and was lowkey bullied (it was actually high key but the teacher downplayed and did nothing)'
offensive	'the world will rejoice when you die. murderer classless' 'destroy our country? more like defending our country against treasonous traitor the white house trumpisatraitor trumptaxes trumpsaninternationaldisgrace trumpmustresign' 'looks like the lying incompetent homophobic racist borisjohnson will the next tory leader...well least we’ll get generalelection boris? borisjohnsonshouldnotbepm torydrugoff toryleadershipcontest https://t.co/ho4hibto7a'

Evaluation

Metrics

Label	Accuracy
all	0.5722

Uses

Direct Use for Inference

First install the SetFit library:

pip install setfit

Then you can load this model and run inference.

from setfit import SetFitModel

# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("Nikhilbendre/my-awesome-setfit-model")
# Run inference
preds = model("this bitch")

Training Details

Training Set Metrics

Training set	Min	Median	Max
Word count	1	31.7855	1331

Label	Training Sample Count
adult content	100
bullying	100
derogatory	100
discrimination	100
gun violence	100
hate	100
offensive	100
physical violence	100
sexual harassment	100
suicide	100
toxic	100

Training Hyperparameters

batch_size: (4, 4)
num_epochs: (10, 10)
max_steps: -1
sampling_strategy: oversampling
num_iterations: 20
body_learning_rate: (2e-05, 2e-05)
head_learning_rate: 2e-05
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	0.2443	-
0.0045	50	0.3281	-
0.0091	100	0.3332	-
0.0136	150	0.2277	-
0.0182	200	0.2349	-
0.0227	250	0.1334	-
0.0273	300	0.2644	-
0.0318	350	0.2592	-
0.0364	400	0.1887	-
0.0409	450	0.1979	-
0.0455	500	0.2129	-
0.05	550	0.0973	-
0.0545	600	0.2668	-
0.0591	650	0.1174	-
0.0636	700	0.1916	-
0.0682	750	0.1189	-
0.0727	800	0.2277	-
0.0773	850	0.1881	-
0.0818	900	0.1465	-
0.0864	950	0.1099	-
0.0909	1000	0.1549	-
0.0955	1050	0.1248	-
0.1	1100	0.1229	-
0.1045	1150	0.1852	-
0.1091	1200	0.0698	-
0.1136	1250	0.1726	-
0.1182	1300	0.1093	-
0.1227	1350	0.1563	-
0.1273	1400	0.1223	-
0.1318	1450	0.0557	-
0.1364	1500	0.1671	-
0.1409	1550	0.0872	-
0.1455	1600	0.0795	-
0.15	1650	0.0429	-
0.1545	1700	0.1217	-
0.1591	1750	0.0094	-
0.1636	1800	0.0463	-
0.1682	1850	0.0842	-
0.1727	1900	0.004	-
0.1773	1950	0.0204	-
0.1818	2000	0.0133	-
0.1864	2050	0.1028	-
0.1909	2100	0.0098	-
0.1955	2150	0.0166	-
0.2	2200	0.0221	-
0.2045	2250	0.0296	-
0.2091	2300	0.024	-
0.2136	2350	0.1014	-
0.2182	2400	0.0035	-
0.2227	2450	0.0086	-
0.2273	2500	0.0092	-
0.2318	2550	0.001	-
0.2364	2600	0.0047	-
0.2409	2650	0.0065	-
0.2455	2700	0.0046	-
0.25	2750	0.0094	-
0.2545	2800	0.004	-
0.2591	2850	0.1082	-
0.2636	2900	0.0022	-
0.2682	2950	0.0026	-
0.2727	3000	0.0009	-
0.2773	3050	0.0008	-
0.2818	3100	0.0004	-
0.2864	3150	0.0012	-
0.2909	3200	0.0005	-
0.2955	3250	0.0021	-
0.3	3300	0.0008	-
0.3045	3350	0.0007	-
0.3091	3400	0.002	-
0.3136	3450	0.0013	-
0.3182	3500	0.0007	-
0.3227	3550	0.0052	-
0.3273	3600	0.0012	-
0.3318	3650	0.0019	-
0.3364	3700	0.0006	-
0.3409	3750	0.0009	-
0.3455	3800	0.0004	-
0.35	3850	0.0039	-
0.3545	3900	0.0005	-
0.3591	3950	0.0086	-
0.3636	4000	0.0002	-
0.3682	4050	0.0014	-
0.3727	4100	0.0006	-
0.3773	4150	0.0012	-
0.3818	4200	0.0008	-
0.3864	4250	0.0008	-
0.3909	4300	0.0004	-
0.3955	4350	0.0003	-
0.4	4400	0.0002	-
0.4045	4450	0.0001	-
0.4091	4500	0.0003	-
0.4136	4550	0.0003	-
0.4182	4600	0.0001	-
0.4227	4650	0.0003	-
0.4273	4700	0.0002	-
0.4318	4750	0.0002	-
0.4364	4800	0.0001	-
0.4409	4850	0.0003	-
0.4455	4900	0.0001	-
0.45	4950	0.0009	-
0.4545	5000	0.0002	-
0.4591	5050	0.0001	-
0.4636	5100	0.0001	-
0.4682	5150	0.0001	-
0.4727	5200	0.0006	-
0.4773	5250	0.0001	-
0.4818	5300	0.0002	-
0.4864	5350	0.0001	-
0.4909	5400	0.0002	-
0.4955	5450	0.0002	-
0.5	5500	0.0002	-
0.5045	5550	0.0002	-
0.5091	5600	0.0006	-
0.5136	5650	0.0001	-
0.5182	5700	0.0001	-
0.5227	5750	0.0002	-
0.5273	5800	0.0001	-
0.5318	5850	0.0013	-
0.5364	5900	0.0002	-
0.5409	5950	0.0003	-
0.5455	6000	0.0002	-
0.55	6050	0.0007	-
0.5545	6100	0.0002	-
0.5591	6150	0.0001	-
0.5636	6200	0.0002	-
0.5682	6250	0.0013	-
0.5727	6300	0.0003	-
0.5773	6350	0.0002	-
0.5818	6400	0.0001	-
0.5864	6450	0.0002	-
0.5909	6500	0.0001	-
0.5955	6550	0.0004	-
0.6	6600	0.0001	-
0.6045	6650	0.0002	-
0.6091	6700	0.0003	-
0.6136	6750	0.0017	-
0.6182	6800	0.0019	-
0.6227	6850	0.0003	-
0.6273	6900	0.001	-
0.6318	6950	0.0001	-
0.6364	7000	0.0002	-
0.6409	7050	0.0007	-
0.6455	7100	0.0001	-
0.65	7150	0.0002	-
0.6545	7200	0.0002	-
0.6591	7250	0.0004	-
0.6636	7300	0.0004	-
0.6682	7350	0.0007	-
0.6727	7400	0.0002	-
0.6773	7450	0.0001	-
0.6818	7500	0.0003	-
0.6864	7550	0.0001	-
0.6909	7600	0.0	-
0.6955	7650	0.0002	-
0.7	7700	0.0005	-
0.7045	7750	0.0002	-
0.7091	7800	0.0	-
0.7136	7850	0.0001	-
0.7182	7900	0.0002	-
0.7227	7950	0.0001	-
0.7273	8000	0.0001	-
0.7318	8050	0.0003	-
0.7364	8100	0.0019	-
0.7409	8150	0.0014	-
0.7455	8200	0.0001	-
0.75	8250	0.0002	-
0.7545	8300	0.0002	-
0.7591	8350	0.0005	-
0.7636	8400	0.0001	-
0.7682	8450	0.0045	-
0.7727	8500	0.0	-
0.7773	8550	0.0002	-
0.7818	8600	0.0008	-
0.7864	8650	0.0003	-
0.7909	8700	0.0001	-
0.7955	8750	0.0001	-
0.8	8800	0.0003	-
0.8045	8850	0.0	-
0.8091	8900	0.0	-
0.8136	8950	0.0001	-
0.8182	9000	0.0	-
0.8227	9050	0.0001	-
0.8273	9100	0.0	-
0.8318	9150	0.0001	-
0.8364	9200	0.0003	-
0.8409	9250	0.0	-
0.8455	9300	0.0	-
0.85	9350	0.0408	-
0.8545	9400	0.0021	-
0.8591	9450	0.1726	-
0.8636	9500	0.1827	-
0.8682	9550	0.0006	-
0.8727	9600	0.0001	-
0.8773	9650	0.0001	-
0.8818	9700	0.0003	-
0.8864	9750	0.0001	-
0.8909	9800	0.0001	-
0.8955	9850	0.0001	-
0.9	9900	0.001	-
0.9045	9950	0.0001	-
0.9091	10000	0.0002	-
0.9136	10050	0.0002	-
0.9182	10100	0.0001	-
0.9227	10150	0.0001	-
0.9273	10200	0.0004	-
0.9318	10250	0.0001	-
0.9364	10300	0.0001	-
0.9409	10350	0.0002	-
0.9455	10400	0.0001	-
0.95	10450	0.0	-
0.9545	10500	0.0001	-
0.9591	10550	0.0001	-
0.9636	10600	0.0002	-
0.9682	10650	0.0001	-
0.9727	10700	0.0	-
0.9773	10750	0.0	-
0.9818	10800	0.0	-
0.9864	10850	0.0	-
0.9909	10900	0.0001	-
0.9955	10950	0.0	-
1.0	11000	0.0	-
1.0045	11050	0.0001	-
1.0091	11100	0.0002	-
1.0136	11150	0.0001	-
1.0182	11200	0.0001	-
1.0227	11250	0.0001	-
1.0273	11300	0.0	-
1.0318	11350	0.0014	-
1.0364	11400	0.0002	-
1.0409	11450	0.0001	-
1.0455	11500	0.0001	-
1.05	11550	0.0001	-
1.0545	11600	0.0	-
1.0591	11650	0.0	-
1.0636	11700	0.0003	-
1.0682	11750	0.0002	-
1.0727	11800	0.0001	-
1.0773	11850	0.0001	-
1.0818	11900	0.0001	-
1.0864	11950	0.0001	-
1.0909	12000	0.0001	-
1.0955	12050	0.0001	-
1.1	12100	0.0002	-
1.1045	12150	0.0001	-
1.1091	12200	0.0698	-
1.1136	12250	0.0001	-
1.1182	12300	0.0001	-
1.1227	12350	0.0002	-
1.1273	12400	0.0002	-
1.1318	12450	0.0002	-
1.1364	12500	0.0	-
1.1409	12550	0.0001	-
1.1455	12600	0.0001	-
1.15	12650	0.0001	-
1.1545	12700	0.0	-
1.1591	12750	0.0004	-
1.1636	12800	0.0001	-
1.1682	12850	0.0001	-
1.1727	12900	0.0	-
1.1773	12950	0.0001	-
1.1818	13000	0.0001	-
1.1864	13050	0.0002	-
1.1909	13100	0.0001	-
1.1955	13150	0.0	-
1.2	13200	0.0001	-
1.2045	13250	0.0002	-
1.2091	13300	0.0	-
1.2136	13350	0.0002	-
1.2182	13400	0.0001	-
1.2227	13450	0.0002	-
1.2273	13500	0.001	-
1.2318	13550	0.0001	-
1.2364	13600	0.0	-
1.2409	13650	0.0001	-
1.2455	13700	0.0	-
1.25	13750	0.0001	-
1.2545	13800	0.0002	-
1.2591	13850	0.0009	-
1.2636	13900	0.0	-
1.2682	13950	0.0001	-
1.2727	14000	0.0	-
1.2773	14050	0.001	-
1.2818	14100	0.0001	-
1.2864	14150	0.0001	-
1.2909	14200	0.0001	-
1.2955	14250	0.0011	-
1.3	14300	0.0003	-
1.3045	14350	0.0449	-
1.3091	14400	0.0004	-
1.3136	14450	0.0219	-
1.3182	14500	0.002	-
1.3227	14550	0.0001	-
1.3273	14600	0.0001	-
1.3318	14650	0.0	-
1.3364	14700	0.0001	-
1.3409	14750	0.0002	-
1.3455	14800	0.0	-
1.35	14850	0.0001	-
1.3545	14900	0.0001	-
1.3591	14950	0.0001	-
1.3636	15000	0.0059	-
1.3682	15050	0.0005	-
1.3727	15100	0.0001	-
1.3773	15150	0.0	-
1.3818	15200	0.0	-
1.3864	15250	0.0	-
1.3909	15300	0.0	-
1.3955	15350	0.0	-
1.4	15400	0.0001	-
1.4045	15450	0.0	-
1.4091	15500	0.0001	-
1.4136	15550	0.0001	-
1.4182	15600	0.0001	-
1.4227	15650	0.0	-
1.4273	15700	0.0	-
1.4318	15750	0.0	-
1.4364	15800	0.0001	-
1.4409	15850	0.0	-
1.4455	15900	0.0001	-
1.45	15950	0.0005	-
1.4545	16000	0.0001	-
1.4591	16050	0.0001	-
1.4636	16100	0.0002	-
1.4682	16150	0.0	-
1.4727	16200	0.0	-
1.4773	16250	0.0001	-
1.4818	16300	0.0002	-
1.4864	16350	0.0	-
1.4909	16400	0.0001	-
1.4955	16450	0.0	-
1.5	16500	0.0	-
1.5045	16550	0.0	-
1.5091	16600	0.0	-
1.5136	16650	0.0001	-
1.5182	16700	0.0	-
1.5227	16750	0.0	-
1.5273	16800	0.0001	-
1.5318	16850	0.0	-
1.5364	16900	0.0	-
1.5409	16950	0.0	-
1.5455	17000	0.0	-
1.55	17050	0.0001	-
1.5545	17100	0.0	-
1.5591	17150	0.0	-
1.5636	17200	0.0	-
1.5682	17250	0.0	-
1.5727	17300	0.0	-
1.5773	17350	0.0	-
1.5818	17400	0.0002	-
1.5864	17450	0.0	-
1.5909	17500	0.0	-
1.5955	17550	0.0	-
1.6	17600	0.0001	-
1.6045	17650	0.0	-
1.6091	17700	0.0	-
1.6136	17750	0.0	-
1.6182	17800	0.0	-
1.6227	17850	0.0	-
1.6273	17900	0.0001	-
1.6318	17950	0.0	-
1.6364	18000	0.0001	-
1.6409	18050	0.0001	-
1.6455	18100	0.0001	-
1.65	18150	0.0	-
1.6545	18200	0.0003	-
1.6591	18250	0.0001	-
1.6636	18300	0.0001	-
1.6682	18350	0.0	-
1.6727	18400	0.0	-
1.6773	18450	0.0	-
1.6818	18500	0.0001	-
1.6864	18550	0.0	-
1.6909	18600	0.0	-
1.6955	18650	0.0	-
1.7	18700	0.0	-
1.7045	18750	0.0001	-
1.7091	18800	0.0001	-
1.7136	18850	0.0001	-
1.7182	18900	0.0	-
1.7227	18950	0.0	-
1.7273	19000	0.0	-
1.7318	19050	0.0001	-
1.7364	19100	0.0	-
1.7409	19150	0.0	-
1.7455	19200	0.0	-
1.75	19250	0.0001	-
1.7545	19300	0.0	-
1.7591	19350	0.0	-
1.7636	19400	0.0002	-
1.7682	19450	0.0001	-
1.7727	19500	0.0001	-
1.7773	19550	0.0	-
1.7818	19600	0.0001	-
1.7864	19650	0.0007	-
1.7909	19700	0.0	-
1.7955	19750	0.0001	-
1.8	19800	0.0002	-
1.8045	19850	0.0	-
1.8091	19900	0.0002	-
1.8136	19950	0.0002	-
1.8182	20000	0.0	-
1.8227	20050	0.0002	-
1.8273	20100	0.0	-
1.8318	20150	0.0	-
1.8364	20200	0.0	-
1.8409	20250	0.0001	-
1.8455	20300	0.0001	-
1.85	20350	0.0	-
1.8545	20400	0.0001	-
1.8591	20450	0.0	-
1.8636	20500	0.0	-
1.8682	20550	0.0	-
1.8727	20600	0.0014	-
1.8773	20650	0.0001	-
1.8818	20700	0.0	-
1.8864	20750	0.0009	-
1.8909	20800	0.0002	-
1.8955	20850	0.0	-
1.9	20900	0.0227	-
1.9045	20950	0.1435	-
1.9091	21000	0.0002	-
1.9136	21050	0.0137	-
1.9182	21100	0.0004	-
1.9227	21150	0.0001	-
1.9273	21200	0.0001	-
1.9318	21250	0.0	-
1.9364	21300	0.0001	-
1.9409	21350	0.0	-
1.9455	21400	0.0	-
1.95	21450	0.0001	-
1.9545	21500	0.0	-
1.9591	21550	0.0	-
1.9636	21600	0.0001	-
1.9682	21650	0.0	-
1.9727	21700	0.0001	-
1.9773	21750	0.0	-
1.9818	21800	0.0	-
1.9864	21850	0.0	-
1.9909	21900	0.0	-
1.9955	21950	0.0001	-
2.0	22000	0.0001	-
2.0045	22050	0.0001	-
2.0091	22100	0.0	-
2.0136	22150	0.0005	-
2.0182	22200	0.0001	-
2.0227	22250	0.0	-
2.0273	22300	0.0001	-
2.0318	22350	0.0002	-
2.0364	22400	0.0042	-
2.0409	22450	0.0147	-
2.0455	22500	0.0	-
2.05	22550	0.0	-
2.0545	22600	0.0	-
2.0591	22650	0.0026	-
2.0636	22700	0.0	-
2.0682	22750	0.0001	-
2.0727	22800	0.0	-
2.0773	22850	0.0	-
2.0818	22900	0.0001	-
2.0864	22950	0.0	-
2.0909	23000	0.0001	-
2.0955	23050	0.0001	-
2.1	23100	0.0	-
2.1045	23150	0.0	-
2.1091	23200	0.0001	-
2.1136	23250	0.0	-
2.1182	23300	0.0	-
2.1227	23350	0.0002	-
2.1273	23400	0.0	-
2.1318	23450	0.0	-
2.1364	23500	0.0001	-
2.1409	23550	0.0	-
2.1455	23600	0.0	-
2.15	23650	0.0	-
2.1545	23700	0.0	-
2.1591	23750	0.0001	-
2.1636	23800	0.0	-
2.1682	23850	0.0	-
2.1727	23900	0.0	-
2.1773	23950	0.0001	-
2.1818	24000	0.0	-
2.1864	24050	0.0	-
2.1909	24100	0.0	-
2.1955	24150	0.0	-
2.2	24200	0.0001	-
2.2045	24250	0.0	-
2.2091	24300	0.0001	-
2.2136	24350	0.0	-
2.2182	24400	0.0	-
2.2227	24450	0.0	-
2.2273	24500	0.0001	-
2.2318	24550	0.0	-
2.2364	24600	0.0	-
2.2409	24650	0.0	-
2.2455	24700	0.0001	-
2.25	24750	0.0001	-
2.2545	24800	0.0	-
2.2591	24850	0.0	-
2.2636	24900	0.0	-
2.2682	24950	0.0	-
2.2727	25000	0.0	-
2.2773	25050	0.0001	-
2.2818	25100	0.0	-
2.2864	25150	0.0	-
2.2909	25200	0.0002	-
2.2955	25250	0.0	-
2.3	25300	0.0	-
2.3045	25350	0.0001	-
2.3091	25400	0.0	-
2.3136	25450	0.0001	-
2.3182	25500	0.0001	-
2.3227	25550	0.0	-
2.3273	25600	0.0	-
2.3318	25650	0.0	-
2.3364	25700	0.0001	-
2.3409	25750	0.0	-
2.3455	25800	0.0002	-
2.35	25850	0.0	-
2.3545	25900	0.0001	-
2.3591	25950	0.0001	-
2.3636	26000	0.0	-
2.3682	26050	0.0002	-
2.3727	26100	0.0	-
2.3773	26150	0.0	-
2.3818	26200	0.0002	-
2.3864	26250	0.0	-
2.3909	26300	0.0004	-
2.3955	26350	0.0	-
2.4	26400	0.0	-
2.4045	26450	0.0	-
2.4091	26500	0.0	-
2.4136	26550	0.0	-
2.4182	26600	0.0	-
2.4227	26650	0.0	-
2.4273	26700	0.0	-
2.4318	26750	0.0001	-
2.4364	26800	0.0	-
2.4409	26850	0.0	-
2.4455	26900	0.0001	-
2.45	26950	0.0	-
2.4545	27000	0.0001	-
2.4591	27050	0.0	-
2.4636	27100	0.0	-
2.4682	27150	0.0	-
2.4727	27200	0.0	-
2.4773	27250	0.0	-
2.4818	27300	0.0001	-
2.4864	27350	0.0	-
2.4909	27400	0.0001	-
2.4955	27450	0.0001	-
2.5	27500	0.0	-
2.5045	27550	0.0	-
2.5091	27600	0.0002	-
2.5136	27650	0.0	-
2.5182	27700	0.0001	-
2.5227	27750	0.0008	-
2.5273	27800	0.0002	-
2.5318	27850	0.0	-
2.5364	27900	0.0001	-
2.5409	27950	0.0001	-
2.5455	28000	0.0	-
2.55	28050	0.0179	-
2.5545	28100	0.0	-
2.5591	28150	0.0001	-
2.5636	28200	0.0	-
2.5682	28250	0.0	-
2.5727	28300	0.0031	-
2.5773	28350	0.0001	-
2.5818	28400	0.0	-
2.5864	28450	0.0	-
2.5909	28500	0.0001	-
2.5955	28550	0.0001	-
2.6	28600	0.0	-
2.6045	28650	0.0	-
2.6091	28700	0.0001	-
2.6136	28750	0.0	-
2.6182	28800	0.0	-
2.6227	28850	0.0	-
2.6273	28900	0.0	-
2.6318	28950	0.0	-
2.6364	29000	0.0001	-
2.6409	29050	0.0001	-
2.6455	29100	0.0	-
2.65	29150	0.0	-
2.6545	29200	0.0	-
2.6591	29250	0.0001	-
2.6636	29300	0.0	-
2.6682	29350	0.0	-
2.6727	29400	0.0	-
2.6773	29450	0.0	-
2.6818	29500	0.0	-
2.6864	29550	0.0	-
2.6909	29600	0.0	-
2.6955	29650	0.0	-
2.7	29700	0.0	-
2.7045	29750	0.0001	-
2.7091	29800	0.0	-
2.7136	29850	0.0	-
2.7182	29900	0.0001	-
2.7227	29950	0.0	-
2.7273	30000	0.0	-
2.7318	30050	0.0001	-
2.7364	30100	0.0001	-
2.7409	30150	0.0	-
2.7455	30200	0.0001	-
2.75	30250	0.0	-
2.7545	30300	0.0005	-
2.7591	30350	0.1041	-
2.7636	30400	0.0049	-
2.7682	30450	0.0264	-
2.7727	30500	0.0	-
2.7773	30550	0.0	-
2.7818	30600	0.2649	-
2.7864	30650	0.0016	-
2.7909	30700	0.0001	-
2.7955	30750	0.0123	-
2.8	30800	0.1437	-
2.8045	30850	0.0	-
2.8091	30900	0.0	-
2.8136	30950	0.0	-
2.8182	31000	0.2468	-
2.8227	31050	0.0	-
2.8273	31100	0.0	-
2.8318	31150	0.0	-
2.8364	31200	0.0	-
2.8409	31250	0.0	-
2.8455	31300	0.2486	-
2.85	31350	0.0001	-
2.8545	31400	0.0001	-
2.8591	31450	0.0	-
2.8636	31500	0.0	-
2.8682	31550	0.0001	-
2.8727	31600	0.0	-
2.8773	31650	0.0	-
2.8818	31700	0.0	-
2.8864	31750	0.0	-
2.8909	31800	0.0	-
2.8955	31850	0.0	-
2.9	31900	0.0	-
2.9045	31950	0.2417	-
2.9091	32000	0.0	-
2.9136	32050	0.2362	-
2.9182	32100	0.0003	-
2.9227	32150	0.0001	-
2.9273	32200	0.0003	-
2.9318	32250	0.0	-
2.9364	32300	0.0001	-
2.9409	32350	0.2468	-
2.9455	32400	0.0	-
2.95	32450	0.0	-
2.9545	32500	0.2505	-
2.9591	32550	0.0232	-
2.9636	32600	0.0001	-
2.9682	32650	0.2462	-
2.9727	32700	0.0001	-
2.9773	32750	0.0042	-
2.9818	32800	0.007	-
2.9864	32850	0.0105	-
2.9909	32900	0.0674	-
2.9955	32950	0.0	-
3.0	33000	0.0	-
3.0045	33050	0.0001	-
3.0091	33100	0.0001	-
3.0136	33150	0.2478	-
3.0182	33200	0.0007	-
3.0227	33250	0.0001	-
3.0273	33300	0.0	-
3.0318	33350	0.0015	-
3.0364	33400	0.0001	-
3.0409	33450	0.0	-
3.0455	33500	0.0001	-
3.05	33550	0.2482	-
3.0545	33600	0.0	-
3.0591	33650	0.0	-
3.0636	33700	0.0	-
3.0682	33750	0.0	-
3.0727	33800	0.0	-
3.0773	33850	0.2484	-
3.0818	33900	0.0036	-
3.0864	33950	0.0	-
3.0909	34000	0.0	-
3.0955	34050	0.0002	-
3.1	34100	0.0001	-
3.1045	34150	0.0001	-
3.1091	34200	0.2471	-
3.1136	34250	0.0	-
3.1182	34300	0.0001	-
3.1227	34350	0.0001	-
3.1273	34400	0.0038	-
3.1318	34450	0.0018	-
3.1364	34500	0.0001	-
3.1409	34550	0.0147	-
3.1455	34600	0.0	-
3.15	34650	0.2478	-
3.1545	34700	0.0025	-
3.1591	34750	0.0	-
3.1636	34800	0.0034	-
3.1682	34850	0.0	-
3.1727	34900	0.0026	-
3.1773	34950	0.0001	-
3.1818	35000	0.0	-
3.1864	35050	0.0001	-
3.1909	35100	0.0003	-
3.1955	35150	0.0	-
3.2	35200	0.0	-
3.2045	35250	0.0001	-
3.2091	35300	0.0002	-
3.2136	35350	0.0	-
3.2182	35400	0.0069	-
3.2227	35450	0.0002	-
3.2273	35500	0.0	-
3.2318	35550	0.0001	-
3.2364	35600	0.0033	-
3.2409	35650	0.0	-
3.2455	35700	0.0001	-
3.25	35750	0.0	-
3.2545	35800	0.0003	-
3.2591	35850	0.0001	-
3.2636	35900	0.0036	-
3.2682	35950	0.0	-
3.2727	36000	0.0	-
3.2773	36050	0.0004	-
3.2818	36100	0.0	-
3.2864	36150	0.0005	-
3.2909	36200	0.0	-
3.2955	36250	0.0	-
3.3	36300	0.0001	-
3.3045	36350	0.0	-
3.3091	36400	0.0	-
3.3136	36450	0.0	-
3.3182	36500	0.0	-
3.3227	36550	0.0001	-
3.3273	36600	0.0	-
3.3318	36650	0.0	-
3.3364	36700	0.0001	-
3.3409	36750	0.0001	-
3.3455	36800	0.0	-
3.35	36850	0.0	-
3.3545	36900	0.0	-
3.3591	36950	0.0	-
3.3636	37000	0.0	-
3.3682	37050	0.0	-
3.3727	37100	0.0	-
3.3773	37150	0.0024	-
3.3818	37200	0.0001	-
3.3864	37250	0.0	-
3.3909	37300	0.0001	-
3.3955	37350	0.0	-
3.4	37400	0.0046	-
3.4045	37450	0.0	-
3.4091	37500	0.0	-
3.4136	37550	0.0002	-
3.4182	37600	0.0	-
3.4227	37650	0.0001	-
3.4273	37700	0.0001	-
3.4318	37750	0.0001	-
3.4364	37800	0.0002	-
3.4409	37850	0.0	-
3.4455	37900	0.0	-
3.45	37950	0.0	-
3.4545	38000	0.0	-
3.4591	38050	0.0003	-
3.4636	38100	0.0	-
3.4682	38150	0.0007	-
3.4727	38200	0.0002	-
3.4773	38250	0.001	-
3.4818	38300	0.0	-
3.4864	38350	0.0	-
3.4909	38400	0.0	-
3.4955	38450	0.0008	-
3.5	38500	0.0	-
3.5045	38550	0.0	-
3.5091	38600	0.0032	-
3.5136	38650	0.0001	-
3.5182	38700	0.0004	-
3.5227	38750	0.0	-
3.5273	38800	0.0001	-
3.5318	38850	0.0001	-
3.5364	38900	0.0	-
3.5409	38950	0.0	-
3.5455	39000	0.0	-
3.55	39050	0.0	-
3.5545	39100	0.0	-
3.5591	39150	0.0	-
3.5636	39200	0.0	-
3.5682	39250	0.0	-
3.5727	39300	0.0	-
3.5773	39350	0.0	-
3.5818	39400	0.0003	-
3.5864	39450	0.0	-
3.5909	39500	0.0	-
3.5955	39550	0.0	-
3.6	39600	0.0004	-
3.6045	39650	0.2547	-
3.6091	39700	0.0001	-
3.6136	39750	0.0001	-
3.6182	39800	0.0002	-
3.6227	39850	0.0001	-
3.6273	39900	0.0	-
3.6318	39950	0.1489	-
3.6364	40000	0.0013	-
3.6409	40050	0.0017	-
3.6455	40100	0.0632	-
3.65	40150	0.0037	-
3.6545	40200	0.0003	-
3.6591	40250	0.0003	-
3.6636	40300	0.0161	-
3.6682	40350	0.0	-
3.6727	40400	0.004	-
3.6773	40450	0.0002	-
3.6818	40500	0.0001	-
3.6864	40550	0.0001	-
3.6909	40600	0.0001	-
3.6955	40650	0.0013	-
3.7	40700	0.0001	-
3.7045	40750	0.0	-
3.7091	40800	0.0001	-
3.7136	40850	0.0	-
3.7182	40900	0.0001	-
3.7227	40950	0.0002	-
3.7273	41000	0.0046	-
3.7318	41050	0.0	-
3.7364	41100	0.1408	-
3.7409	41150	0.0002	-
3.7455	41200	0.0252	-
3.75	41250	0.0	-
3.7545	41300	0.0002	-
3.7591	41350	0.0001	-
3.7636	41400	0.2435	-
3.7682	41450	0.0	-
3.7727	41500	0.0027	-
3.7773	41550	0.0007	-
3.7818	41600	0.0	-
3.7864	41650	0.0022	-
3.7909	41700	0.0004	-
3.7955	41750	0.0	-
3.8	41800	0.0	-
3.8045	41850	0.2471	-
3.8091	41900	0.0	-
3.8136	41950	0.0	-
3.8182	42000	0.0	-
3.8227	42050	0.0001	-
3.8273	42100	0.0001	-
3.8318	42150	0.0	-
3.8364	42200	0.0	-
3.8409	42250	0.0	-
3.8455	42300	0.0	-
3.85	42350	0.0003	-
3.8545	42400	0.0	-
3.8591	42450	0.0	-
3.8636	42500	0.0013	-
3.8682	42550	0.0	-
3.8727	42600	0.0003	-
3.8773	42650	0.1858	-
3.8818	42700	0.0	-
3.8864	42750	0.0197	-
3.8909	42800	0.0	-
3.8955	42850	0.0051	-
3.9	42900	0.0	-
3.9045	42950	0.0004	-
3.9091	43000	0.0014	-
3.9136	43050	0.0026	-
3.9182	43100	0.0	-
3.9227	43150	0.0	-
3.9273	43200	0.0011	-
3.9318	43250	0.2407	-
3.9364	43300	0.0	-
3.9409	43350	0.0	-
3.9455	43400	0.0001	-
3.95	43450	0.0036	-
3.9545	43500	0.0008	-
3.9591	43550	0.0001	-
3.9636	43600	0.0	-
3.9682	43650	0.0001	-
3.9727	43700	0.0	-
3.9773	43750	0.0	-
3.9818	43800	0.0	-
3.9864	43850	0.0	-
3.9909	43900	0.2426	-
3.9955	43950	0.0001	-
4.0	44000	0.0	-
4.0045	44050	0.0	-
4.0091	44100	0.0	-
4.0136	44150	0.0022	-
4.0182	44200	0.0	-
4.0227	44250	0.0	-
4.0273	44300	0.0	-
4.0318	44350	0.0	-
4.0364	44400	0.0132	-
4.0409	44450	0.0	-
4.0455	44500	0.0	-
4.05	44550	0.0	-
4.0545	44600	0.0	-
4.0591	44650	0.0001	-
4.0636	44700	0.0042	-
4.0682	44750	0.0	-
4.0727	44800	0.0	-
4.0773	44850	0.0001	-
4.0818	44900	0.0	-
4.0864	44950	0.0	-
4.0909	45000	0.0026	-
4.0955	45050	0.0001	-
4.1	45100	0.0001	-
4.1045	45150	0.0	-
4.1091	45200	0.0	-
4.1136	45250	0.0034	-
4.1182	45300	0.0001	-
4.1227	45350	0.2462	-
4.1273	45400	0.2459	-
4.1318	45450	0.0002	-
4.1364	45500	0.0001	-
4.1409	45550	0.0	-
4.1455	45600	0.0002	-
4.15	45650	0.0001	-
4.1545	45700	0.0	-
4.1591	45750	0.0	-
4.1636	45800	0.0	-
4.1682	45850	0.001	-
4.1727	45900	0.0065	-
4.1773	45950	0.0002	-
4.1818	46000	0.0001	-
4.1864	46050	0.0001	-
4.1909	46100	0.0	-
4.1955	46150	0.0	-
4.2	46200	0.0001	-
4.2045	46250	0.0	-
4.2091	46300	0.0	-
4.2136	46350	0.0	-
4.2182	46400	0.2457	-
4.2227	46450	0.0001	-
4.2273	46500	0.0001	-
4.2318	46550	0.0	-
4.2364	46600	0.0053	-
4.2409	46650	0.0001	-
4.2455	46700	0.0	-
4.25	46750	0.0	-
4.2545	46800	0.0009	-
4.2591	46850	0.0	-
4.2636	46900	0.0001	-
4.2682	46950	0.0	-
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4.2773	47050	0.0	-
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10.0	110000	0.0	-

Framework Versions

Python: 3.10.12
SetFit: 1.0.1
Sentence Transformers: 2.2.2
Transformers: 4.36.0
PyTorch: 2.0.0
Datasets: 2.15.0
Tokenizers: 0.15.0

Citation

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}
}

Nikhilbendre
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my-awesome-setfit-model