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CrisisNarratives
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setfit-9classes-single_label

Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results
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SetFit with sentence-transformers/paraphrase-mpnet-base-v2

This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/paraphrase-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:

  1. Fine-tuning a Sentence Transformer with contrastive learning.
  2. Training a classification head with features from the fine-tuned Sentence Transformer.

Model Details

Model Description

Model Sources

Model Labels

Label Examples
5
  • 'please show us the evidence I asked for'
  • 'Please follow https://youtu.be/WpTCt-S-qLM ??'
  • 'Answer the question. The first is illegal in NY, the second is legal.'
0
  • 'This guy sounds like he needs to clear his throat'
  • 'If only most senates in the US can see how climate change can not only effect our planets environment, it also our economys like theirs.'
  • '1st Comment!'
7
  • 'Yeah I can do that.'
  • "I can totally accept that the government fund green energy, it's for the best."
  • 'Yes, he is right ! My Dr. did exactly what he is saying. He started antibiotics then 5 days started the steroids. Hopefully other dr will do the same.'
2
  • 'ok boomer'
  • 'I can see where ur coming from she did invite this cousin to live there which mind you is likely an act of kindness, and it is ur private space. But tbh you are also being extremely petty, this man is on the couch, he has early morning shifts, using ur bathroom would not disturb a single person, while using ur roommates means this man has to be very uncomfortable walk through a sleeping persons room every morning and sneak back out again. Likely waking up the cousin in the process. Thats why I believe its an Everyone Sucks here cause theyre both asshole like moves.'
  • 'suggesting the vaccine to women who are pregnant, when it can cause for many women earlier heavier longer periods, means it triggers a period, we know women in our personal lives that have experienced that along with their period coming twice that month, and we know to avoid foods that can trigger a period because that could potentially cause a miscarriage, so why suggest it?? this is how the whole world will lose confidence in science and medicine because they can down right lie to our face claiming they understand more then you meanwhile propagating the agenda of pharmaceutical companies. absaloutly disgusting and shame on you for betraying our trust.'
3
  • 'Nothing is hotter than Shawn, not even the sun mate??'
  • 'No Im not trolling.'
  • "I'm not being hurtful. I'm being honest. You need to vaccinate your cat"
6
  • 'So youre taking a government course?'
  • 'Is this journalist on work experience ?'
  • 'Who is here after the movie'
4
  • 'Forward looking required now, which the leaders are doing and doing their best, sleep deprived and a world of responsibility on them. Thanks to all'
  • "Oh, great, you could do that? That'd help me out really."
  • "Couldn't be more proud and happy that these heroes are finally taking a stand to the horrible ways the current government is pushing the country"
1
  • "Maybe STOP paying commanders who have NEVER even picked up a hose and give the power back to the brigades CAPTAIN'S. And things will start to get better, from someone who is actually doing something. Snowy mountains Australia."
  • "@Keith Bawden You have an education in science? Me too! Did you study in any field relevant to the topic? I am currently doing a PhD in biogeochemistry, and my research group is involved in climate science. I can tell you the VAST majority of scientists in fields directly related to or peripheral to climate change accept that it is indeed a real phenomenon, and it is caused by humans. The exceptions you can name are exactly that, exceptions. I'll grant you, Zarkhova may be right about a coming grand solar minimum, but even if so, all it would do is slightly slow temperature increase. There would be no mini ice age (Fuelner and Rahmstorf, 2010). The question is, in 2-3 years, when a 'mini ice age' does not occur, will you change your mind, or find some other reason to deny?"
  • "You should have gotten herd immunity in Changi, considering 95% efficacy of Pfizer and 80% or more are vaccinated.\r\nIt's either the efficacy is faked or the vaccine is useless against the indian variant."
8
  • "Things got out of hand, I'm sorry."
  • 'Oh no, I did not mean it that way, it was completely misunderstood what I was saying. Didnt mean to offend you, sorry!'
  • 'Sorry.'

Evaluation

Metrics

Label Metric
all 0.4483

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("CrisisNarratives/setfit-9classes-single_label")
# Run inference
preds = model("my dad had huge ones..so they may be real..")

Training Details

Training Set Metrics

Training set Min Median Max
Word count 1 25.8891 1681
Label Training Sample Count
0 156
1 81
2 64
3 52
4 46
5 63
6 35
7 37
8 7

Training Hyperparameters

  • batch_size: (16, 16)
  • num_epochs: (3, 3)
  • max_steps: -1
  • sampling_strategy: oversampling
  • num_iterations: 40
  • body_learning_rate: (1.752e-05, 1.752e-05)
  • head_learning_rate: 1.752e-05
  • loss: CosineSimilarityLoss
  • distance_metric: cosine_distance
  • margin: 0.25
  • end_to_end: False
  • use_amp: False
  • warmup_proportion: 0.1
  • seed: 30
  • eval_max_steps: -1
  • load_best_model_at_end: False

Training Results

Epoch Step Training Loss Validation Loss
0.0004 1 0.3913 -
0.0185 50 0.3901 -
0.0370 100 0.219 -
0.0555 150 0.2308 -
0.0739 200 0.2161 -
0.0924 250 0.2 -
0.1109 300 0.2436 -
0.1294 350 0.2219 -
0.1479 400 0.1266 -
0.1664 450 0.1043 -
0.1848 500 0.076 -
0.2033 550 0.1331 -
0.2218 600 0.0858 -
0.2403 650 0.0355 -
0.2588 700 0.0475 -
0.2773 750 0.066 -
0.2957 800 0.0667 -
0.3142 850 0.0082 -
0.3327 900 0.0658 -
0.3512 950 0.0042 -
0.3697 1000 0.095 -
0.3882 1050 0.0598 -
0.4067 1100 0.0037 -
0.4251 1150 0.0155 -
0.4436 1200 0.0028 -
0.4621 1250 0.0025 -
0.4806 1300 0.0542 -
0.4991 1350 0.001 -
0.5176 1400 0.0056 -
0.5360 1450 0.001 -
0.5545 1500 0.0011 -
0.5730 1550 0.0007 -
0.5915 1600 0.0014 -
0.6100 1650 0.0018 -
0.6285 1700 0.0012 -
0.6470 1750 0.0005 -
0.6654 1800 0.0006 -
0.6839 1850 0.0003 -
0.7024 1900 0.0002 -
0.7209 1950 0.0044 -
0.7394 2000 0.003 -
0.7579 2050 0.0005 -
0.7763 2100 0.0006 -
0.7948 2150 0.0005 -
0.8133 2200 0.0002 -
0.8318 2250 0.0003 -
0.8503 2300 0.0003 -
0.8688 2350 0.0006 -
0.8872 2400 0.0002 -
0.9057 2450 0.002 -
0.9242 2500 0.0003 -
0.9427 2550 0.0002 -
0.9612 2600 0.0009 -
0.9797 2650 0.0001 -
0.9982 2700 0.0002 -
1.0166 2750 0.0003 -
1.0351 2800 0.0003 -
1.0536 2850 0.0004 -
1.0721 2900 0.0003 -
1.0906 2950 0.0004 -
1.1091 3000 0.0003 -
1.1275 3050 0.0001 -
1.1460 3100 0.0002 -
1.1645 3150 0.0005 -
1.1830 3200 0.0004 -
1.2015 3250 0.0003 -
1.2200 3300 0.0003 -
1.2384 3350 0.0004 -
1.2569 3400 0.0003 -
1.2754 3450 0.0002 -
1.2939 3500 0.0002 -
1.3124 3550 0.0003 -
1.3309 3600 0.0005 -
1.3494 3650 0.0002 -
1.3678 3700 0.0003 -
1.3863 3750 0.0002 -
1.4048 3800 0.0001 -
1.4233 3850 0.0001 -
1.4418 3900 0.0004 -
1.4603 3950 0.0001 -
1.4787 4000 0.0002 -
1.4972 4050 0.001 -
1.5157 4100 0.0002 -
1.5342 4150 0.0003 -
1.5527 4200 0.0001 -
1.5712 4250 0.0001 -
1.5896 4300 0.0002 -
1.6081 4350 0.0005 -
1.6266 4400 0.0001 -
1.6451 4450 0.0002 -
1.6636 4500 0.0001 -
1.6821 4550 0.0001 -
1.7006 4600 0.0001 -
1.7190 4650 0.0001 -
1.7375 4700 0.0001 -
1.7560 4750 0.0002 -
1.7745 4800 0.0001 -
1.7930 4850 0.0001 -
1.8115 4900 0.0001 -
1.8299 4950 0.0 -
1.8484 5000 0.0001 -
1.8669 5050 0.0001 -
1.8854 5100 0.0001 -
1.9039 5150 0.0001 -
1.9224 5200 0.0001 -
1.9409 5250 0.0001 -
1.9593 5300 0.0001 -
1.9778 5350 0.0 -
1.9963 5400 0.0001 -
2.0148 5450 0.0001 -
2.0333 5500 0.0001 -
2.0518 5550 0.0001 -
2.0702 5600 0.0002 -
2.0887 5650 0.0001 -
2.1072 5700 0.0001 -
2.1257 5750 0.0 -
2.1442 5800 0.0001 -
2.1627 5850 0.0001 -
2.1811 5900 0.0003 -
2.1996 5950 0.0001 -
2.2181 6000 0.0002 -
2.2366 6050 0.0001 -
2.2551 6100 0.0001 -
2.2736 6150 0.0001 -
2.2921 6200 0.0001 -
2.3105 6250 0.0001 -
2.3290 6300 0.0001 -
2.3475 6350 0.0001 -
2.3660 6400 0.0001 -
2.3845 6450 0.0001 -
2.4030 6500 0.0001 -
2.4214 6550 0.0001 -
2.4399 6600 0.0001 -
2.4584 6650 0.0001 -
2.4769 6700 0.0001 -
2.4954 6750 0.0001 -
2.5139 6800 0.0001 -
2.5323 6850 0.0002 -
2.5508 6900 0.0001 -
2.5693 6950 0.0002 -
2.5878 7000 0.0001 -
2.6063 7050 0.0001 -
2.6248 7100 0.0 -
2.6433 7150 0.0 -
2.6617 7200 0.0001 -
2.6802 7250 0.0001 -
2.6987 7300 0.0002 -
2.7172 7350 0.0001 -
2.7357 7400 0.0001 -
2.7542 7450 0.0002 -
2.7726 7500 0.0 -
2.7911 7550 0.0001 -
2.8096 7600 0.0005 -
2.8281 7650 0.0001 -
2.8466 7700 0.0001 -
2.8651 7750 0.0001 -
2.8835 7800 0.0002 -
2.9020 7850 0.0 -
2.9205 7900 0.0001 -
2.9390 7950 0.0 -
2.9575 8000 0.0001 -
2.9760 8050 0.0001 -
2.9945 8100 0.0001 -
0.0002 1 0.0001 -
0.0108 50 0.0003 -
0.0216 100 0.0001 -
0.0323 150 0.0004 -
0.0431 200 0.0002 -
0.0539 250 0.0006 -
0.0647 300 0.0001 -
0.0755 350 0.0002 -
0.0862 400 0.0051 -
0.0970 450 0.1866 -
0.1078 500 0.11 -
0.1186 550 0.1214 -
0.1294 600 0.2073 -
0.1401 650 0.019 -
0.1509 700 0.0762 -
0.1617 750 0.1901 -
0.1725 800 0.1234 -
0.1833 850 0.0601 -
0.1940 900 0.4192 -
0.2048 950 0.0397 -
0.2156 1000 0.111 -
0.2264 1050 0.055 -
0.2372 1100 0.0146 -
0.2480 1150 0.1277 -
0.2587 1200 0.0236 -
0.2695 1250 0.0087 -
0.2803 1300 0.2315 -
0.2911 1350 0.3547 -
0.3019 1400 0.5957 -
0.3126 1450 0.2253 -
0.3234 1500 0.2068 -
0.3342 1550 0.3203 -
0.3450 1600 0.5608 -
0.3558 1650 0.3014 -
0.3665 1700 0.3287 -
0.3773 1750 0.3206 -
0.3881 1800 0.4245 -
0.3989 1850 0.2641 -
0.4097 1900 0.4057 -
0.4204 1950 0.3891 -
0.4312 2000 0.3688 -
0.4420 2050 0.4642 -
0.4528 2100 0.3684 -
0.4636 2150 0.246 -
0.4743 2200 0.177 -
0.4851 2250 0.3416 -
0.4959 2300 0.3931 -
0.5067 2350 0.2617 -
0.5175 2400 0.5679 -
0.5282 2450 0.3879 -
0.5390 2500 0.3916 -
0.5498 2550 0.3657 -
0.5606 2600 0.3382 -
0.5714 2650 0.4621 -
0.5821 2700 0.3235 -
0.5929 2750 0.2986 -
0.6037 2800 0.3001 -
0.6145 2850 0.2309 -
0.6253 2900 0.1802 -
0.6361 2950 0.2648 -
0.6468 3000 0.2875 -
0.6576 3050 0.2888 -
0.6684 3100 0.2563 -
0.6792 3150 0.3129 -
0.6900 3200 0.2229 -
0.7007 3250 0.2462 -
0.7115 3300 0.283 -
0.7223 3350 0.3622 -
0.7331 3400 0.3428 -
0.7439 3450 0.4274 -
0.7546 3500 0.4131 -
0.7654 3550 0.2123 -
0.7762 3600 0.326 -
0.7870 3650 0.2488 -
0.7978 3700 0.4046 -
0.8085 3750 0.2664 -
0.8193 3800 0.2426 -
0.8301 3850 0.3534 -
0.8409 3900 0.2753 -
0.8517 3950 0.3177 -
0.8624 4000 0.222 -
0.8732 4050 0.3942 -
0.8840 4100 0.1932 -
0.8948 4150 0.2727 -
0.9056 4200 0.2713 -
0.9163 4250 0.3888 -
0.9271 4300 0.3155 -
0.9379 4350 0.2727 -
0.9487 4400 0.4148 -
0.9595 4450 0.297 -
0.9702 4500 0.2154 -
0.9810 4550 0.2617 -
0.9918 4600 0.255 -
1.0026 4650 0.395 -
1.0134 4700 0.4104 -
1.0241 4750 0.2675 -
1.0349 4800 0.2458 -
1.0457 4850 0.316 -
1.0565 4900 0.3786 -
1.0673 4950 0.2206 -
1.0781 5000 0.3946 -
1.0888 5050 0.2178 -
1.0996 5100 0.302 -
1.1104 5150 0.2449 -
1.1212 5200 0.2644 -
1.1320 5250 0.3111 -
1.1427 5300 0.3953 -
1.1535 5350 0.2064 -
1.1643 5400 0.3149 -
1.1751 5450 0.2073 -
1.1859 5500 0.3759 -
1.1966 5550 0.2044 -
1.2074 5600 0.2034 -
1.2182 5650 0.2325 -
1.2290 5700 0.2393 -
1.2398 5750 0.3568 -
1.2505 5800 0.2234 -
1.2613 5850 0.2428 -
1.2721 5900 0.3561 -
1.2829 5950 0.1885 -
1.2937 6000 0.3153 -
1.3044 6050 0.2288 -
1.3152 6100 0.2852 -
1.3260 6150 0.289 -
1.3368 6200 0.3719 -
1.3476 6250 0.1921 -
1.3583 6300 0.266 -
1.3691 6350 0.2743 -
1.3799 6400 0.3637 -
1.3907 6450 0.3849 -
1.4015 6500 0.1926 -
1.4122 6550 0.3594 -
1.4230 6600 0.3263 -
1.4338 6650 0.4645 -
1.4446 6700 0.2304 -
1.4554 6750 0.2337 -
1.4661 6800 0.2812 -
1.4769 6850 0.2975 -
1.4877 6900 0.4025 -
1.4985 6950 0.1897 -
1.5093 7000 0.4523 -
1.5201 7050 0.1906 -
1.5308 7100 0.2756 -
1.5416 7150 0.3313 -
1.5524 7200 0.2999 -
1.5632 7250 0.2517 -
1.5740 7300 0.2421 -
1.5847 7350 0.2864 -
1.5955 7400 0.3119 -
1.6063 7450 0.2178 -
1.6171 7500 0.4006 -
1.6279 7550 0.2744 -
1.6386 7600 0.2306 -
1.6494 7650 0.2772 -
1.6602 7700 0.2103 -
1.6710 7750 0.3151 -
1.6818 7800 0.3457 -
1.6925 7850 0.2146 -
1.7033 7900 0.2105 -
1.7141 7950 0.1986 -
1.7249 8000 0.2604 -
1.7357 8050 0.1683 -
1.7464 8100 0.2814 -
1.7572 8150 0.2088 -
1.7680 8200 0.3935 -
1.7788 8250 0.3019 -
1.7896 8300 0.3094 -
1.8003 8350 0.2024 -
1.8111 8400 0.2901 -
1.8219 8450 0.2392 -
1.8327 8500 0.3296 -
1.8435 8550 0.2818 -
1.8542 8600 0.2898 -
1.8650 8650 0.2598 -
1.8758 8700 0.3531 -
1.8866 8750 0.2989 -
1.8974 8800 0.2356 -
1.9082 8850 0.3657 -
1.9189 8900 0.3765 -
1.9297 8950 0.2668 -
1.9405 9000 0.4219 -
1.9513 9050 0.3362 -
1.9621 9100 0.325 -
1.9728 9150 0.267 -
1.9836 9200 0.2945 -
1.9944 9250 0.2129 -
2.0052 9300 0.351 -
2.0160 9350 0.4508 -
2.0267 9400 0.2375 -
2.0375 9450 0.2669 -
2.0483 9500 0.232 -
2.0591 9550 0.2469 -
2.0699 9600 0.2644 -
2.0806 9650 0.239 -
2.0914 9700 0.3189 -
2.1022 9750 0.2711 -
2.1130 9800 0.2627 -
2.1238 9850 0.2213 -
2.1345 9900 0.2311 -
2.1453 9950 0.3009 -
2.1561 10000 0.2068 -
2.1669 10050 0.3129 -
2.1777 10100 0.2901 -
2.1884 10150 0.2743 -
2.1992 10200 0.2809 -
2.2100 10250 0.249 -
2.2208 10300 0.3017 -
2.2316 10350 0.4271 -
2.2423 10400 0.2551 -
2.2531 10450 0.1911 -
2.2639 10500 0.3297 -
2.2747 10550 0.3251 -
2.2855 10600 0.267 -
2.2962 10650 0.3022 -
2.3070 10700 0.2353 -
2.3178 10750 0.3533 -
2.3286 10800 0.216 -
2.3394 10850 0.3003 -
2.3502 10900 0.2943 -
2.3609 10950 0.2959 -
2.3717 11000 0.3203 -
2.3825 11050 0.2962 -
2.3933 11100 0.2475 -
2.4041 11150 0.2933 -
2.4148 11200 0.2903 -
2.4256 11250 0.328 -
2.4364 11300 0.1893 -
2.4472 11350 0.2367 -
2.4580 11400 0.2473 -
2.4687 11450 0.2751 -
2.4795 11500 0.2708 -
2.4903 11550 0.3104 -
2.5011 11600 0.2791 -
2.5119 11650 0.3181 -
2.5226 11700 0.2411 -
2.5334 11750 0.3114 -
2.5442 11800 0.2759 -
2.5550 11850 0.3006 -
2.5658 11900 0.2647 -
2.5765 11950 0.225 -
2.5873 12000 0.2904 -
2.5981 12050 0.2776 -
2.6089 12100 0.3102 -
2.6197 12150 0.2499 -
2.6304 12200 0.2763 -
2.6412 12250 0.2645 -
2.6520 12300 0.3281 -
2.6628 12350 0.1793 -
2.6736 12400 0.3369 -
2.6843 12450 0.2598 -
2.6951 12500 0.3334 -
2.7059 12550 0.2935 -
2.7167 12600 0.4243 -
2.7275 12650 0.2212 -
2.7382 12700 0.2187 -
2.7490 12750 0.3004 -
2.7598 12800 0.4244 -
2.7706 12850 0.2242 -
2.7814 12900 0.3072 -
2.7922 12950 0.3468 -
2.8029 13000 0.2112 -
2.8137 13050 0.2935 -
2.8245 13100 0.2618 -
2.8353 13150 0.266 -
2.8461 13200 0.2458 -
2.8568 13250 0.2244 -
2.8676 13300 0.2764 -
2.8784 13350 0.2262 -
2.8892 13400 0.2232 -
2.9000 13450 0.2353 -
2.9107 13500 0.3661 -
2.9215 13550 0.1905 -
2.9323 13600 0.3493 -
2.9431 13650 0.2481 -
2.9539 13700 0.23 -
2.9646 13750 0.2407 -
2.9754 13800 0.2673 -
2.9862 13850 0.2091 -
2.9970 13900 0.2471 -
0.0004 1 0.287 -
0.0185 50 0.285 -
0.0370 100 0.233 -
0.0555 150 0.2874 -
0.0739 200 0.2599 -
0.0924 250 0.284 -
0.1109 300 0.3046 -
0.1294 350 0.2751 -
0.1479 400 0.2343 -
0.1664 450 0.2809 -
0.1848 500 0.2178 -
0.2033 550 0.2654 -
0.2218 600 0.2673 -
0.2403 650 0.2628 -
0.2588 700 0.279 -
0.2773 750 0.2448 -
0.2957 800 0.2502 -
0.3142 850 0.3343 -
0.3327 900 0.2669 -
0.3512 950 0.2714 -
0.3697 1000 0.3234 -
0.3882 1050 0.2892 -
0.4067 1100 0.2437 -
0.4251 1150 0.2409 -
0.4436 1200 0.2402 -
0.4621 1250 0.2479 -
0.4806 1300 0.2323 -
0.4991 1350 0.2474 -
0.5176 1400 0.319 -
0.5360 1450 0.3341 -
0.5545 1500 0.3162 -
0.5730 1550 0.2973 -
0.5915 1600 0.2975 -
0.6100 1650 0.2828 -
0.6285 1700 0.2625 -
0.6470 1750 0.2769 -
0.6654 1800 0.271 -
0.6839 1850 0.2538 -
0.7024 1900 0.1979 -
0.7209 1950 0.3117 -
0.7394 2000 0.2247 -
0.7579 2050 0.3248 -
0.7763 2100 0.2515 -
0.7948 2150 0.2877 -
0.8133 2200 0.3182 -
0.8318 2250 0.2772 -
0.8503 2300 0.2423 -
0.8688 2350 0.2638 -
0.8872 2400 0.226 -
0.9057 2450 0.306 -
0.9242 2500 0.2072 -
0.9427 2550 0.2434 -
0.9612 2600 0.2712 -
0.9797 2650 0.3225 -
0.9982 2700 0.2534 -
1.0166 2750 0.2364 -
1.0351 2800 0.241 -
1.0536 2850 0.2165 -
1.0721 2900 0.2719 -
1.0906 2950 0.2694 -
1.1091 3000 0.2562 -
1.1275 3050 0.2994 -
1.1460 3100 0.2477 -
1.1645 3150 0.231 -
1.1830 3200 0.2751 -
1.2015 3250 0.2543 -
1.2200 3300 0.2468 -
1.2384 3350 0.217 -
1.2569 3400 0.2664 -
1.2754 3450 0.2556 -
1.2939 3500 0.2334 -
1.3124 3550 0.2396 -
1.3309 3600 0.2383 -
1.3494 3650 0.2635 -
1.3678 3700 0.2652 -
1.3863 3750 0.2573 -
1.4048 3800 0.2211 -
1.4233 3850 0.2244 -
1.4418 3900 0.2399 -
1.4603 3950 0.2587 -
1.4787 4000 0.304 -
1.4972 4050 0.287 -
1.5157 4100 0.2667 -
1.5342 4150 0.3251 -
1.5527 4200 0.2641 -
1.5712 4250 0.2576 -
1.5896 4300 0.3057 -
1.6081 4350 0.2145 -
1.6266 4400 0.2665 -
1.6451 4450 0.2756 -
1.6636 4500 0.3089 -
1.6821 4550 0.3013 -
1.7006 4600 0.2337 -
1.7190 4650 0.2538 -
1.7375 4700 0.2428 -
1.7560 4750 0.2694 -
1.7745 4800 0.2367 -
1.7930 4850 0.2656 -
1.8115 4900 0.2405 -
1.8299 4950 0.2381 -
1.8484 5000 0.2363 -
1.8669 5050 0.2395 -
1.8854 5100 0.3183 -
1.9039 5150 0.2918 -
1.9224 5200 0.2985 -
1.9409 5250 0.3331 -
1.9593 5300 0.2716 -
1.9778 5350 0.2529 -
1.9963 5400 0.2557 -
2.0148 5450 0.2618 -
2.0333 5500 0.296 -
2.0518 5550 0.2866 -
2.0702 5600 0.2445 -
2.0887 5650 0.2464 -
2.1072 5700 0.2247 -
2.1257 5750 0.2906 -
2.1442 5800 0.2413 -
2.1627 5850 0.2805 -
2.1811 5900 0.2777 -
2.1996 5950 0.2151 -
2.2181 6000 0.2938 -
2.2366 6050 0.2569 -
2.2551 6100 0.2523 -
2.2736 6150 0.2649 -
2.2921 6200 0.2265 -
2.3105 6250 0.216 -
2.3290 6300 0.3309 -
2.3475 6350 0.2815 -
2.3660 6400 0.2566 -
2.3845 6450 0.237 -
2.4030 6500 0.2165 -
2.4214 6550 0.2975 -
2.4399 6600 0.2402 -
2.4584 6650 0.2943 -
2.4769 6700 0.2522 -
2.4954 6750 0.2473 -
2.5139 6800 0.2652 -
2.5323 6850 0.244 -
2.5508 6900 0.2488 -
2.5693 6950 0.2726 -
2.5878 7000 0.2282 -
2.6063 7050 0.2386 -
2.6248 7100 0.3269 -
2.6433 7150 0.2401 -
2.6617 7200 0.284 -
2.6802 7250 0.3263 -
2.6987 7300 0.3019 -
2.7172 7350 0.2364 -
2.7357 7400 0.2219 -
2.7542 7450 0.2798 -
2.7726 7500 0.2605 -
2.7911 7550 0.2958 -
2.8096 7600 0.2028 -
2.8281 7650 0.2577 -
2.8466 7700 0.2686 -
2.8651 7750 0.2894 -
2.8835 7800 0.3136 -
2.9020 7850 0.2417 -
2.9205 7900 0.276 -
2.9390 7950 0.2608 -
2.9575 8000 0.2545 -
2.9760 8050 0.2539 -
2.9945 8100 0.1995 -

Framework Versions

  • Python: 3.9.16
  • SetFit: 1.0.1
  • Sentence Transformers: 2.2.2
  • Transformers: 4.35.0
  • PyTorch: 2.1.0+cu121
  • Datasets: 2.14.6
  • Tokenizers: 0.14.1

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}
}
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