Hugging Face's logo

mann2107
/
BCMPIIRAB_MiniLM_HTTest

Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results
Model card Files Community
Edit model card

SetFit with sentence-transformers/paraphrase-MiniLM-L6-v2

This is a SetFit model that can be used for Text Classification. This SetFit model uses sentence-transformers/paraphrase-MiniLM-L6-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

Evaluation

Metrics

Label Silhouette_Score
all 0.6826

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("mann2107/BCMPIIRAB_MiniLM_HTTest")
# Run inference
preds = model("Hello, Good morning, would you mind cancelling this rental car?")

Training Details

Training Set Metrics

Training set Min Median Max
Word count 1 25.6577 136
Label Training Sample Count
0 24
1 24
2 24
3 24
4 24
5 24
6 24
7 24
8 24
9 24
10 24
11 24
12 24
13 24

Training Hyperparameters

  • batch_size: (8, 8)
  • num_epochs: (3, 3)
  • max_steps: -1
  • sampling_strategy: oversampling
  • num_iterations: 100
  • body_learning_rate: (3e-05, 3e-05)
  • head_learning_rate: 3e-05
  • loss: MultipleNegativesRankingLoss
  • distance_metric: cosine_distance
  • margin: 0.25
  • end_to_end: False
  • use_amp: True
  • warmup_proportion: 0.1
  • l2_weight: 0.01
  • seed: 42
  • eval_max_steps: -1
  • load_best_model_at_end: False

Training Results

Epoch Step Training Loss Validation Loss
0.0001 1 2.5259 -
0.0060 50 2.8997 -
0.0119 100 2.8192 -
0.0179 150 2.8803 -
0.0238 200 2.635 -
0.0298 250 2.5501 -
0.0357 300 2.4468 -
0.0417 350 2.1309 -
0.0476 400 2.0439 -
0.0536 450 1.9429 -
0.0595 500 1.9344 -
0.0655 550 1.8493 -
0.0714 600 1.7907 -
0.0774 650 1.7712 -
0.0833 700 1.7349 -
0.0893 750 1.7783 -
0.0952 800 1.7022 -
0.1012 850 1.6757 -
0.1071 900 1.709 -
0.1131 950 1.6231 -
0.1190 1000 1.6647 -
0.125 1050 1.7618 -
0.1310 1100 1.652 -
0.1369 1150 1.5564 -
0.1429 1200 1.7067 -
0.1488 1250 1.664 -
0.1548 1300 1.7426 -
0.1607 1350 1.6281 -
0.1667 1400 1.6375 -
0.1726 1450 1.6216 -
0.1786 1500 1.5998 -
0.1845 1550 1.4892 -
0.1905 1600 1.556 -
0.1964 1650 1.6657 -
0.2024 1700 1.6113 -
0.2083 1750 1.634 -
0.2143 1800 1.6615 -
0.2202 1850 1.5192 -
0.2262 1900 1.5846 -
0.2321 1950 1.5376 -
0.2381 2000 1.6028 -
0.2440 2050 1.5744 -
0.25 2100 1.645 -
0.2560 2150 1.5432 -
0.2619 2200 1.5922 -
0.2679 2250 1.612 -
0.2738 2300 1.6553 -
0.2798 2350 1.5797 -
0.2857 2400 1.5249 -
0.2917 2450 1.639 -
0.2976 2500 1.7246 -
0.3036 2550 1.6186 -
0.3095 2600 1.537 -
0.3155 2650 1.5701 -
0.3214 2700 1.6095 -
0.3274 2750 1.5344 -
0.3333 2800 1.6029 -
0.3393 2850 1.6141 -
0.3452 2900 1.5655 -
0.3512 2950 1.5892 -
0.3571 3000 1.595 -
0.3631 3050 1.5068 -
0.3690 3100 1.5826 -
0.375 3150 1.481 -
0.3810 3200 1.6001 -
0.3869 3250 1.4991 -
0.3929 3300 1.605 -
0.3988 3350 1.6154 -
0.4048 3400 1.5516 -
0.4107 3450 1.559 -
0.4167 3500 1.559 -
0.4226 3550 1.5725 -
0.4286 3600 1.5719 -
0.4345 3650 1.4918 -
0.4405 3700 1.5816 -
0.4464 3750 1.5017 -
0.4524 3800 1.5093 -
0.4583 3850 1.5705 -
0.4643 3900 1.5584 -
0.4702 3950 1.5328 -
0.4762 4000 1.4932 -
0.4821 4050 1.5907 -
0.4881 4100 1.5339 -
0.4940 4150 1.4954 -
0.5 4200 1.5256 -
0.5060 4250 1.5349 -
0.5119 4300 1.5238 -
0.5179 4350 1.5222 -
0.5238 4400 1.6318 -
0.5298 4450 1.5872 -
0.5357 4500 1.4892 -
0.5417 4550 1.5764 -
0.5476 4600 1.6123 -
0.5536 4650 1.4708 -
0.5595 4700 1.5201 -
0.5655 4750 1.4975 -
0.5714 4800 1.5402 -
0.5774 4850 1.5396 -
0.5833 4900 1.5325 -
0.5893 4950 1.5166 -
0.5952 5000 1.5216 -
0.6012 5050 1.5934 -
0.6071 5100 1.5118 -
0.6131 5150 1.6581 -
0.6190 5200 1.4251 -
0.625 5250 1.5259 -
0.6310 5300 1.4854 -
0.6369 5350 1.6242 -
0.6429 5400 1.5234 -
0.6488 5450 1.4594 -
0.6548 5500 1.5513 -
0.6607 5550 1.3946 -
0.6667 5600 1.4795 -
0.6726 5650 1.5203 -
0.6786 5700 1.5137 -
0.6845 5750 1.5305 -
0.6905 5800 1.4958 -
0.6964 5850 1.5028 -
0.7024 5900 1.419 -
0.7083 5950 1.5043 -
0.7143 6000 1.4512 -
0.7202 6050 1.5199 -
0.7262 6100 1.5097 -
0.7321 6150 1.4989 -
0.7381 6200 1.4632 -
0.7440 6250 1.4781 -
0.75 6300 1.4592 -
0.7560 6350 1.507 -
0.7619 6400 1.5535 -
0.7679 6450 1.3831 -
0.7738 6500 1.572 -
0.7798 6550 1.5461 -
0.7857 6600 1.5142 -
0.7917 6650 1.494 -
0.7976 6700 1.5487 -
0.8036 6750 1.4344 -
0.8095 6800 1.5262 -
0.8155 6850 1.4942 -
0.8214 6900 1.54 -
0.8274 6950 1.518 -
0.8333 7000 1.5765 -
0.8393 7050 1.5526 -
0.8452 7100 1.5548 -
0.8512 7150 1.3953 -
0.8571 7200 1.5273 -
0.8631 7250 1.4349 -
0.8690 7300 1.4176 -
0.875 7350 1.5242 -
0.8810 7400 1.5263 -
0.8869 7450 1.5435 -
0.8929 7500 1.4882 -
0.8988 7550 1.4965 -
0.9048 7600 1.5185 -
0.9107 7650 1.5739 -
0.9167 7700 1.5821 -
0.9226 7750 1.6197 -
0.9286 7800 1.5154 -
0.9345 7850 1.5844 -
0.9405 7900 1.5242 -
0.9464 7950 1.488 -
0.9524 8000 1.5414 -
0.9583 8050 1.4829 -
0.9643 8100 1.5162 -
0.9702 8150 1.4136 -
0.9762 8200 1.36 -
0.9821 8250 1.5511 -
0.9881 8300 1.4908 -
0.9940 8350 1.5312 -
1.0 8400 1.5008 -
1.0060 8450 1.4283 -
1.0119 8500 1.5027 -
1.0179 8550 1.48 -
1.0238 8600 1.425 -
1.0298 8650 1.5233 -
1.0357 8700 1.4259 -
1.0417 8750 1.4355 -
1.0476 8800 1.5006 -
1.0536 8850 1.511 -
1.0595 8900 1.3043 -
1.0655 8950 1.5039 -
1.0714 9000 1.4909 -
1.0774 9050 1.4493 -
1.0833 9100 1.4877 -
1.0893 9150 1.5232 -
1.0952 9200 1.6282 -
1.1012 9250 1.4438 -
1.1071 9300 1.5234 -
1.1131 9350 1.5368 -
1.1190 9400 1.5029 -
1.125 9450 1.4776 -
1.1310 9500 1.4877 -
1.1369 9550 1.4917 -
1.1429 9600 1.4474 -
1.1488 9650 1.3519 -
1.1548 9700 1.5118 -
1.1607 9750 1.5507 -
1.1667 9800 1.4395 -
1.1726 9850 1.4883 -
1.1786 9900 1.4524 -
1.1845 9950 1.4756 -
1.1905 10000 1.5255 -
1.1964 10050 1.4795 -
1.2024 10100 1.5277 -
1.2083 10150 1.477 -
1.2143 10200 1.4438 -
1.2202 10250 1.5517 -
1.2262 10300 1.588 -
1.2321 10350 1.5352 -
1.2381 10400 1.3697 -
1.2440 10450 1.4449 -
1.25 10500 1.4473 -
1.2560 10550 1.5566 -
1.2619 10600 1.4502 -
1.2679 10650 1.4821 -
1.2738 10700 1.4296 -
1.2798 10750 1.4801 -
1.2857 10800 1.4542 -
1.2917 10850 1.4258 -
1.2976 10900 1.4142 -
1.3036 10950 1.6023 -
1.3095 11000 1.4291 -
1.3155 11050 1.5386 -
1.3214 11100 1.4433 -
1.3274 11150 1.4218 -
1.3333 11200 1.4345 -
1.3393 11250 1.5321 -
1.3452 11300 1.5001 -
1.3512 11350 1.3381 -
1.3571 11400 1.4819 -
1.3631 11450 1.4676 -
1.3690 11500 1.5056 -
1.375 11550 1.5052 -
1.3810 11600 1.5217 -
1.3869 11650 1.391 -
1.3929 11700 1.46 -
1.3988 11750 1.5022 -
1.4048 11800 1.4579 -
1.4107 11850 1.5025 -
1.4167 11900 1.5058 -
1.4226 11950 1.5107 -
1.4286 12000 1.5327 -
1.4345 12050 1.4727 -
1.4405 12100 1.4353 -
1.4464 12150 1.42 -
1.4524 12200 1.5349 -
1.4583 12250 1.473 -
1.4643 12300 1.5228 -
1.4702 12350 1.498 -
1.4762 12400 1.4321 -
1.4821 12450 1.5058 -
1.4881 12500 1.4601 -
1.4940 12550 1.5346 -
1.5 12600 1.5985 -
1.5060 12650 1.4683 -
1.5119 12700 1.5088 -
1.5179 12750 1.5082 -
1.5238 12800 1.5784 -
1.5298 12850 1.5241 -
1.5357 12900 1.434 -
1.5417 12950 1.452 -
1.5476 13000 1.4459 -
1.5536 13050 1.4965 -
1.5595 13100 1.5313 -
1.5655 13150 1.4781 -
1.5714 13200 1.5502 -
1.5774 13250 1.4602 -
1.5833 13300 1.4477 -
1.5893 13350 1.4736 -
1.5952 13400 1.5035 -
1.6012 13450 1.4829 -
1.6071 13500 1.4941 -
1.6131 13550 1.5462 -
1.6190 13600 1.4764 -
1.625 13650 1.4838 -
1.6310 13700 1.4264 -
1.6369 13750 1.6312 -
1.6429 13800 1.4323 -
1.6488 13850 1.514 -
1.6548 13900 1.3944 -
1.6607 13950 1.4709 -
1.6667 14000 1.4268 -
1.6726 14050 1.5699 -
1.6786 14100 1.5433 -
1.6845 14150 1.431 -
1.6905 14200 1.5421 -
1.6964 14250 1.4854 -
1.7024 14300 1.4341 -
1.7083 14350 1.4321 -
1.7143 14400 1.4284 -
1.7202 14450 1.4725 -
1.7262 14500 1.5744 -
1.7321 14550 1.4892 -
1.7381 14600 1.5357 -
1.7440 14650 1.4536 -
1.75 14700 1.4861 -
1.7560 14750 1.5268 -
1.7619 14800 1.4613 -
1.7679 14850 1.4313 -
1.7738 14900 1.4522 -
1.7798 14950 1.4291 -
1.7857 15000 1.5054 -
1.7917 15050 1.495 -
1.7976 15100 1.5352 -
1.8036 15150 1.4803 -
1.8095 15200 1.3922 -
1.8155 15250 1.4879 -
1.8214 15300 1.4752 -
1.8274 15350 1.5102 -
1.8333 15400 1.4474 -
1.8393 15450 1.4939 -
1.8452 15500 1.5216 -
1.8512 15550 1.4656 -
1.8571 15600 1.5171 -
1.8631 15650 1.3437 -
1.8690 15700 1.4875 -
1.875 15750 1.4692 -
1.8810 15800 1.4804 -
1.8869 15850 1.4423 -
1.8929 15900 1.4592 -
1.8988 15950 1.5764 -
1.9048 16000 1.4083 -
1.9107 16050 1.4852 -
1.9167 16100 1.5158 -
1.9226 16150 1.4602 -
1.9286 16200 1.4465 -
1.9345 16250 1.412 -
1.9405 16300 1.483 -
1.9464 16350 1.5342 -
1.9524 16400 1.3866 -
1.9583 16450 1.4318 -
1.9643 16500 1.6241 -
1.9702 16550 1.5514 -
1.9762 16600 1.46 -
1.9821 16650 1.4069 -
1.9881 16700 1.457 -
1.9940 16750 1.4273 -
2.0 16800 1.3673 -
2.0060 16850 1.3753 -
2.0119 16900 1.4279 -
2.0179 16950 1.3897 -
2.0238 17000 1.4659 -
2.0298 17050 1.4494 -
2.0357 17100 1.4533 -
2.0417 17150 1.3735 -
2.0476 17200 1.4232 -
2.0536 17250 1.4229 -
2.0595 17300 1.4597 -
2.0655 17350 1.4825 -
2.0714 17400 1.4661 -
2.0774 17450 1.4332 -
2.0833 17500 1.5895 -
2.0893 17550 1.4824 -
2.0952 17600 1.4472 -
2.1012 17650 1.4001 -
2.1071 17700 1.4638 -
2.1131 17750 1.4651 -
2.1190 17800 1.4711 -
2.125 17850 1.4474 -
2.1310 17900 1.4544 -
2.1369 17950 1.3935 -
2.1429 18000 1.4449 -
2.1488 18050 1.4671 -
2.1548 18100 1.4169 -
2.1607 18150 1.5095 -
2.1667 18200 1.4186 -
2.1726 18250 1.4574 -
2.1786 18300 1.4448 -
2.1845 18350 1.5045 -
2.1905 18400 1.4998 -
2.1964 18450 1.3559 -
2.2024 18500 1.4862 -
2.2083 18550 1.4018 -
2.2143 18600 1.4407 -
2.2202 18650 1.5812 -
2.2262 18700 1.4268 -
2.2321 18750 1.4434 -
2.2381 18800 1.5467 -
2.2440 18850 1.4281 -
2.25 18900 1.482 -
2.2560 18950 1.5261 -
2.2619 19000 1.4152 -
2.2679 19050 1.5267 -
2.2738 19100 1.4237 -
2.2798 19150 1.5455 -
2.2857 19200 1.4679 -
2.2917 19250 1.3398 -
2.2976 19300 1.4697 -
2.3036 19350 1.4176 -
2.3095 19400 1.4661 -
2.3155 19450 1.4397 -
2.3214 19500 1.5095 -
2.3274 19550 1.4873 -
2.3333 19600 1.4312 -
2.3393 19650 1.441 -
2.3452 19700 1.4341 -
2.3512 19750 1.4229 -
2.3571 19800 1.4917 -
2.3631 19850 1.4397 -
2.3690 19900 1.4027 -
2.375 19950 1.5022 -
2.3810 20000 1.441 -
2.3869 20050 1.4392 -
2.3929 20100 1.4454 -
2.3988 20150 1.4886 -
2.4048 20200 1.4776 -
2.4107 20250 1.3946 -
2.4167 20300 1.5492 -
2.4226 20350 1.534 -
2.4286 20400 1.4011 -
2.4345 20450 1.5276 -
2.4405 20500 1.4633 -
2.4464 20550 1.4446 -
2.4524 20600 1.5005 -
2.4583 20650 1.4818 -
2.4643 20700 1.4319 -
2.4702 20750 1.4406 -
2.4762 20800 1.4496 -
2.4821 20850 1.4963 -
2.4881 20900 1.4731 -
2.4940 20950 1.4536 -
2.5 21000 1.5153 -
2.5060 21050 1.5522 -
2.5119 21100 1.3759 -
2.5179 21150 1.4285 -
2.5238 21200 1.4162 -
2.5298 21250 1.4383 -
2.5357 21300 1.4408 -
2.5417 21350 1.4009 -
2.5476 21400 1.4589 -
2.5536 21450 1.4478 -
2.5595 21500 1.4876 -
2.5655 21550 1.4206 -
2.5714 21600 1.4927 -
2.5774 21650 1.5047 -
2.5833 21700 1.3988 -
2.5893 21750 1.4714 -
2.5952 21800 1.3605 -
2.6012 21850 1.5635 -
2.6071 21900 1.4678 -
2.6131 21950 1.4618 -
2.6190 22000 1.4407 -
2.625 22050 1.5451 -
2.6310 22100 1.4844 -
2.6369 22150 1.4088 -
2.6429 22200 1.5056 -
2.6488 22250 1.4678 -
2.6548 22300 1.4262 -
2.6607 22350 1.4492 -
2.6667 22400 1.4463 -
2.6726 22450 1.3851 -
2.6786 22500 1.513 -
2.6845 22550 1.45 -
2.6905 22600 1.4382 -
2.6964 22650 1.4637 -
2.7024 22700 1.4487 -
2.7083 22750 1.4507 -
2.7143 22800 1.5065 -
2.7202 22850 1.4116 -
2.7262 22900 1.479 -
2.7321 22950 1.444 -
2.7381 23000 1.4056 -
2.7440 23050 1.3913 -
2.75 23100 1.5108 -
2.7560 23150 1.4092 -
2.7619 23200 1.4341 -
2.7679 23250 1.4274 -
2.7738 23300 1.4748 -
2.7798 23350 1.3819 -
2.7857 23400 1.5012 -
2.7917 23450 1.3594 -
2.7976 23500 1.4708 -
2.8036 23550 1.4425 -
2.8095 23600 1.3566 -
2.8155 23650 1.456 -
2.8214 23700 1.5937 -
2.8274 23750 1.3835 -
2.8333 23800 1.4137 -
2.8393 23850 1.3861 -
2.8452 23900 1.4249 -
2.8512 23950 1.3599 -
2.8571 24000 1.4789 -
2.8631 24050 1.4527 -
2.8690 24100 1.4406 -
2.875 24150 1.4301 -
2.8810 24200 1.4059 -
2.8869 24250 1.5052 -
2.8929 24300 1.4429 -
2.8988 24350 1.5183 -
2.9048 24400 1.4288 -
2.9107 24450 1.4673 -
2.9167 24500 1.4582 -
2.9226 24550 1.4792 -
2.9286 24600 1.4598 -
2.9345 24650 1.4785 -
2.9405 24700 1.4259 -
2.9464 24750 1.4877 -
2.9524 24800 1.5162 -
2.9583 24850 1.4854 -
2.9643 24900 1.3679 -
2.9702 24950 1.3985 -
2.9762 25000 1.421 -
2.9821 25050 1.5048 -
2.9881 25100 1.4618 -
2.9940 25150 1.5061 -
3.0 25200 1.3634 -

Framework Versions

  • Python: 3.12.0
  • SetFit: 1.2.0.dev0
  • Sentence Transformers: 3.2.1
  • Transformers: 4.45.2
  • PyTorch: 2.5.0+cpu
  • Datasets: 3.0.2
  • Tokenizers: 0.20.1

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}
}
Downloads last month
36
Safetensors
Model size
22.7M params
Tensor type
F32
·
Inference Examples
Text Classification
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for mann2107/BCMPIIRAB_MiniLM_HTTest

Base model

sentence-transformers/paraphrase-MiniLM-L6-v2
Finetuned
(5)
this model

Evaluation results

View on Papers With Code