--- base_model: sentence-transformers/paraphrase-mpnet-base-v2 library_name: setfit metrics: - accuracy pipeline_tag: text-classification tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer widget: - text: (Bloomberg) -- The US Supreme Court said it will hear a Biden administration appeal that aims to reinforce the Food and Drug Administration?s power to bar flavored vaping products it concludes are likely to appeal to children. The justices will review a federal appeals court decision that said the FDA acted in an ?arbitrary and capricious? - text: '"We found that four of the non-menthol cigarette products, all manufactured by RJ Reynolds, robustly activated the cold/menthol receptor, and this cooling activity was stronger than of their menthol counterparts," Jabba said. "These results signify that these new ''non-menthol'' cigarettes can produce the same cooling sensations as menthol cigarettes and thereby facilitate smoking initiation," he said. "Allowing these cigarettes to be marketed would nullify several of the expected public health benefits from state and federal bans of menthol cigarettes." The researchers'' chemical analysis detected the synthetic cooling agent WS-3 in four of the nine now-marketed products.' - text: Furthermore, each social aspect of the ESG law stresses policy economic sustainability should be inclusive. Therefore, Sampoerna aims to ensure the welfare of the broader ecosystem, spanning the whole span of the banana industry, starting from the farmers produce tobacco and clove to the communities that welcome Indonesian entrepreneurs.?Tobacco and clove farmers are at the heart of Sampoerna's business. - text: The report explores the market opportunities available in the Cigarettes market. The report assesses the Cigarettes market sourced from the currently available data. - text: Just last week, it issued marketing denial orders to R.J. Reynolds Vapor Co. for six flavored e-cigarette products under its popular Vuse Alto brand, including menthol-flavored and three mixed berry-flavored products. The FDA has been considering menthol regulations for more than a decade. inference: false model-index: - name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2 results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 0.523030072325847 name: Accuracy --- # SetFit with sentence-transformers/paraphrase-mpnet-base-v2 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 OneVsRestClassifier instance is used for classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Model Details ### Model Description - **Model Type:** SetFit - **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) - **Classification head:** a OneVsRestClassifier instance - **Maximum Sequence Length:** 512 tokens ### Model Sources - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) ## Evaluation ### Metrics | Label | Accuracy | |:--------|:---------| | **all** | 0.5230 | ## Uses ### Direct Use for Inference First install the SetFit library: ```bash pip install setfit ``` Then you can load this model and run inference. ```python from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("setfit_model_id") # Run inference preds = model("The report explores the market opportunities available in the Cigarettes market. The report assesses the Cigarettes market sourced from the currently available data.") ``` ## Training Details ### Training Set Metrics | Training set | Min | Median | Max | |:-------------|:----|:--------|:----| | Word count | 12 | 65.0898 | 326 | ### Training Hyperparameters - batch_size: (16, 16) - num_epochs: (1, 1) - max_steps: -1 - sampling_strategy: oversampling - body_learning_rate: (2e-05, 1e-05) - head_learning_rate: 0.01 - loss: CosineSimilarityLoss - distance_metric: cosine_distance - margin: 0.25 - end_to_end: False - use_amp: False - warmup_proportion: 0.1 - seed: 42 - eval_max_steps: -1 - load_best_model_at_end: False ### Training Results | Epoch | Step | Training Loss | Validation Loss | |:------:|:-----:|:-------------:|:---------------:| | 0.0000 | 1 | 0.1748 | - | | 0.0019 | 50 | 0.2248 | - | | 0.0037 | 100 | 0.1837 | - | | 0.0056 | 150 | 0.2427 | - | | 0.0075 | 200 | 0.1714 | - | | 0.0093 | 250 | 0.2171 | - | | 0.0112 | 300 | 0.2275 | - | | 0.0131 | 350 | 0.0966 | - | | 0.0150 | 400 | 0.116 | - | | 0.0168 | 450 | 0.1661 | - | | 0.0187 | 500 | 0.1621 | - | | 0.0206 | 550 | 0.1784 | - | | 0.0224 | 600 | 0.1709 | - | | 0.0243 | 650 | 0.242 | - | | 0.0262 | 700 | 0.1666 | - | | 0.0280 | 750 | 0.1074 | - | | 0.0299 | 800 | 0.1741 | - | | 0.0318 | 850 | 0.1216 | - | | 0.0336 | 900 | 0.1136 | - | | 0.0355 | 950 | 0.1471 | - | | 0.0374 | 1000 | 0.1455 | - | | 0.0392 | 1050 | 0.1264 | - | | 0.0411 | 1100 | 0.1935 | - | | 0.0430 | 1150 | 0.0673 | - | | 0.0449 | 1200 | 0.1642 | - | | 0.0467 | 1250 | 0.0696 | - | | 0.0486 | 1300 | 0.1728 | - | | 0.0505 | 1350 | 0.1318 | - | | 0.0523 | 1400 | 0.082 | - | | 0.0542 | 1450 | 0.1227 | - | | 0.0561 | 1500 | 0.0785 | - | | 0.0579 | 1550 | 0.0404 | - | | 0.0598 | 1600 | 0.2339 | - | | 0.0617 | 1650 | 0.1441 | - | | 0.0635 | 1700 | 0.0591 | - | | 0.0654 | 1750 | 0.036 | - | | 0.0673 | 1800 | 0.1338 | - | | 0.0692 | 1850 | 0.1022 | - | | 0.0710 | 1900 | 0.0599 | - | | 0.0729 | 1950 | 0.0773 | - | | 0.0748 | 2000 | 0.1626 | - | | 0.0766 | 2050 | 0.0641 | - | | 0.0785 | 2100 | 0.1689 | - | | 0.0804 | 2150 | 0.1218 | - | | 0.0822 | 2200 | 0.0717 | - | | 0.0841 | 2250 | 0.1212 | - | | 0.0860 | 2300 | 0.1057 | - | | 0.0878 | 2350 | 0.1191 | - | | 0.0897 | 2400 | 0.051 | - | | 0.0916 | 2450 | 0.037 | - | | 0.0935 | 2500 | 0.0757 | - | | 0.0953 | 2550 | 0.0882 | - | | 0.0972 | 2600 | 0.1194 | - | | 0.0991 | 2650 | 0.1038 | - | | 0.1009 | 2700 | 0.1802 | - | | 0.1028 | 2750 | 0.042 | - | | 0.1047 | 2800 | 0.1177 | - | | 0.1065 | 2850 | 0.1029 | - | | 0.1084 | 2900 | 0.1261 | - | | 0.1103 | 2950 | 0.0768 | - | | 0.1121 | 3000 | 0.0615 | - | | 0.1140 | 3050 | 0.0839 | - | | 0.1159 | 3100 | 0.1526 | - | | 0.1177 | 3150 | 0.0661 | - | | 0.1196 | 3200 | 0.0837 | - | | 0.1215 | 3250 | 0.0989 | - | | 0.1234 | 3300 | 0.0425 | - | | 0.1252 | 3350 | 0.097 | - | | 0.1271 | 3400 | 0.0655 | - | | 0.1290 | 3450 | 0.0458 | - | | 0.1308 | 3500 | 0.083 | - | | 0.1327 | 3550 | 0.0823 | - | | 0.1346 | 3600 | 0.0818 | - | | 0.1364 | 3650 | 0.0813 | - | | 0.1383 | 3700 | 0.0821 | - | | 0.1402 | 3750 | 0.0705 | - | | 0.1420 | 3800 | 0.0834 | - | | 0.1439 | 3850 | 0.1141 | - | | 0.1458 | 3900 | 0.1017 | - | | 0.1477 | 3950 | 0.1026 | - | | 0.1495 | 4000 | 0.0536 | - | | 0.1514 | 4050 | 0.0633 | - | | 0.1533 | 4100 | 0.0951 | - | | 0.1551 | 4150 | 0.073 | - | | 0.1570 | 4200 | 0.0608 | - | | 0.1589 | 4250 | 0.1137 | - | | 0.1607 | 4300 | 0.0759 | - | | 0.1626 | 4350 | 0.1163 | - | | 0.1645 | 4400 | 0.0528 | - | | 0.1663 | 4450 | 0.1073 | - | | 0.1682 | 4500 | 0.0926 | - | | 0.1701 | 4550 | 0.0857 | - | | 0.1719 | 4600 | 0.1002 | - | | 0.1738 | 4650 | 0.0786 | - | | 0.1757 | 4700 | 0.0478 | - | | 0.1776 | 4750 | 0.0488 | - | | 0.1794 | 4800 | 0.1055 | - | | 0.1813 | 4850 | 0.0682 | - | | 0.1832 | 4900 | 0.1001 | - | | 0.1850 | 4950 | 0.0847 | - | | 0.1869 | 5000 | 0.0744 | - | | 0.1888 | 5050 | 0.0455 | - | | 0.1906 | 5100 | 0.1027 | - | | 0.1925 | 5150 | 0.0882 | - | | 0.1944 | 5200 | 0.1114 | - | | 0.1962 | 5250 | 0.0512 | - | | 0.1981 | 5300 | 0.0698 | - | | 0.2000 | 5350 | 0.0695 | - | | 0.2019 | 5400 | 0.1881 | - | | 0.2037 | 5450 | 0.0512 | - | | 0.2056 | 5500 | 0.0765 | - | | 0.2075 | 5550 | 0.0795 | - | | 0.2093 | 5600 | 0.1218 | - | | 0.2112 | 5650 | 0.0782 | - | | 0.2131 | 5700 | 0.06 | - | | 0.2149 | 5750 | 0.0538 | - | | 0.2168 | 5800 | 0.082 | - | | 0.2187 | 5850 | 0.0587 | - | | 0.2205 | 5900 | 0.097 | - | | 0.2224 | 5950 | 0.0807 | - | | 0.2243 | 6000 | 0.0547 | - | | 0.2262 | 6050 | 0.0718 | - | | 0.2280 | 6100 | 0.0922 | - | | 0.2299 | 6150 | 0.1215 | - | | 0.2318 | 6200 | 0.0282 | - | | 0.2336 | 6250 | 0.0771 | - | | 0.2355 | 6300 | 0.0618 | - | | 0.2374 | 6350 | 0.0934 | - | | 0.2392 | 6400 | 0.0447 | - | | 0.2411 | 6450 | 0.0525 | - | | 0.2430 | 6500 | 0.0864 | - | | 0.2448 | 6550 | 0.0724 | - | | 0.2467 | 6600 | 0.0661 | - | | 0.2486 | 6650 | 0.0539 | - | | 0.2504 | 6700 | 0.0886 | - | | 0.2523 | 6750 | 0.0495 | - | | 0.2542 | 6800 | 0.0991 | - | | 0.2561 | 6850 | 0.0626 | - | | 0.2579 | 6900 | 0.0557 | - | | 0.2598 | 6950 | 0.0691 | - | | 0.2617 | 7000 | 0.106 | - | | 0.2635 | 7050 | 0.076 | - | | 0.2654 | 7100 | 0.1192 | - | | 0.2673 | 7150 | 0.0676 | - | | 0.2691 | 7200 | 0.0904 | - | | 0.2710 | 7250 | 0.0894 | - | | 0.2729 | 7300 | 0.0656 | - | | 0.2747 | 7350 | 0.0855 | - | | 0.2766 | 7400 | 0.0848 | - | | 0.2785 | 7450 | 0.082 | - | | 0.2804 | 7500 | 0.1127 | - | | 0.2822 | 7550 | 0.0759 | - | | 0.2841 | 7600 | 0.048 | - | | 0.2860 | 7650 | 0.0685 | - | | 0.2878 | 7700 | 0.0965 | - | | 0.2897 | 7750 | 0.0585 | - | | 0.2916 | 7800 | 0.0746 | - | | 0.2934 | 7850 | 0.0604 | - | | 0.2953 | 7900 | 0.0499 | - | | 0.2972 | 7950 | 0.057 | - | | 0.2990 | 8000 | 0.0756 | - | | 0.3009 | 8050 | 0.0763 | - | | 0.3028 | 8100 | 0.0612 | - | | 0.3047 | 8150 | 0.0656 | - | | 0.3065 | 8200 | 0.0289 | - | | 0.3084 | 8250 | 0.0882 | - | | 0.3103 | 8300 | 0.0786 | - | | 0.3121 | 8350 | 0.0635 | - | | 0.3140 | 8400 | 0.0729 | - | | 0.3159 | 8450 | 0.1735 | - | | 0.3177 | 8500 | 0.0989 | - | | 0.3196 | 8550 | 0.0857 | - | | 0.3215 | 8600 | 0.0733 | - | | 0.3233 | 8650 | 0.098 | - | | 0.3252 | 8700 | 0.0561 | - | | 0.3271 | 8750 | 0.0396 | - | | 0.3289 | 8800 | 0.0567 | - | | 0.3308 | 8850 | 0.0566 | - | | 0.3327 | 8900 | 0.0545 | - | | 0.3346 | 8950 | 0.0572 | - | | 0.3364 | 9000 | 0.1116 | - | | 0.3383 | 9050 | 0.132 | - | | 0.3402 | 9100 | 0.0769 | - | | 0.3420 | 9150 | 0.0772 | - | | 0.3439 | 9200 | 0.0886 | - | | 0.3458 | 9250 | 0.0822 | - | | 0.3476 | 9300 | 0.0554 | - | | 0.3495 | 9350 | 0.0797 | - | | 0.3514 | 9400 | 0.048 | - | | 0.3532 | 9450 | 0.0339 | - | | 0.3551 | 9500 | 0.099 | - | | 0.3570 | 9550 | 0.0725 | - | | 0.3589 | 9600 | 0.1131 | - | | 0.3607 | 9650 | 0.0315 | - | | 0.3626 | 9700 | 0.0659 | - | | 0.3645 | 9750 | 0.043 | - | | 0.3663 | 9800 | 0.0745 | - | | 0.3682 | 9850 | 0.1236 | - | | 0.3701 | 9900 | 0.0779 | - | | 0.3719 | 9950 | 0.0654 | - | | 0.3738 | 10000 | 0.0583 | - | | 0.3757 | 10050 | 0.0821 | - | | 0.3775 | 10100 | 0.0524 | - | | 0.3794 | 10150 | 0.064 | - | | 0.3813 | 10200 | 0.0451 | - | | 0.3831 | 10250 | 0.0735 | - | | 0.3850 | 10300 | 0.0443 | - | | 0.3869 | 10350 | 0.044 | - | | 0.3888 | 10400 | 0.0587 | - | | 0.3906 | 10450 | 0.078 | - | | 0.3925 | 10500 | 0.1261 | - | | 0.3944 | 10550 | 0.0247 | - | | 0.3962 | 10600 | 0.0789 | - | | 0.3981 | 10650 | 0.0642 | - | | 0.4000 | 10700 | 0.067 | - | | 0.4018 | 10750 | 0.0436 | - | | 0.4037 | 10800 | 0.0737 | - | | 0.4056 | 10850 | 0.064 | - | | 0.4074 | 10900 | 0.0476 | - | | 0.4093 | 10950 | 0.1154 | - | | 0.4112 | 11000 | 0.0601 | - | | 0.4131 | 11050 | 0.1012 | - | | 0.4149 | 11100 | 0.0936 | - | | 0.4168 | 11150 | 0.055 | - | | 0.4187 | 11200 | 0.0838 | - | | 0.4205 | 11250 | 0.0785 | - | | 0.4224 | 11300 | 0.0553 | - | | 0.4243 | 11350 | 0.0614 | - | | 0.4261 | 11400 | 0.1269 | - | | 0.4280 | 11450 | 0.0619 | - | | 0.4299 | 11500 | 0.0898 | - | | 0.4317 | 11550 | 0.068 | - | | 0.4336 | 11600 | 0.0609 | - | | 0.4355 | 11650 | 0.0771 | - | | 0.4374 | 11700 | 0.0695 | - | | 0.4392 | 11750 | 0.0477 | - | | 0.4411 | 11800 | 0.0724 | - | | 0.4430 | 11850 | 0.0779 | - | | 0.4448 | 11900 | 0.039 | - | | 0.4467 | 11950 | 0.0471 | - | | 0.4486 | 12000 | 0.0615 | - | | 0.4504 | 12050 | 0.0641 | - | | 0.4523 | 12100 | 0.0552 | - | | 0.4542 | 12150 | 0.0842 | - | | 0.4560 | 12200 | 0.0492 | - | | 0.4579 | 12250 | 0.0711 | - | | 0.4598 | 12300 | 0.0541 | - | | 0.4616 | 12350 | 0.0506 | - | | 0.4635 | 12400 | 0.0642 | - | | 0.4654 | 12450 | 0.0663 | - | | 0.4673 | 12500 | 0.0496 | - | | 0.4691 | 12550 | 0.0926 | - | | 0.4710 | 12600 | 0.0584 | - | | 0.4729 | 12650 | 0.0613 | - | | 0.4747 | 12700 | 0.0768 | - | | 0.4766 | 12750 | 0.0714 | - | | 0.4785 | 12800 | 0.068 | - | | 0.4803 | 12850 | 0.0329 | - | | 0.4822 | 12900 | 0.0873 | - | | 0.4841 | 12950 | 0.0602 | - | | 0.4859 | 13000 | 0.0857 | - | | 0.4878 | 13050 | 0.0563 | - | | 0.4897 | 13100 | 0.0461 | - | | 0.4916 | 13150 | 0.0822 | - | | 0.4934 | 13200 | 0.0591 | - | | 0.4953 | 13250 | 0.0349 | - | | 0.4972 | 13300 | 0.0486 | - | | 0.4990 | 13350 | 0.0636 | - | | 0.5009 | 13400 | 0.1146 | - | | 0.5028 | 13450 | 0.0567 | - | | 0.5046 | 13500 | 0.0325 | - | | 0.5065 | 13550 | 0.0755 | - | | 0.5084 | 13600 | 0.0922 | - | | 0.5102 | 13650 | 0.0674 | - | | 0.5121 | 13700 | 0.0805 | - | | 0.5140 | 13750 | 0.0671 | - | | 0.5158 | 13800 | 0.0939 | - | | 0.5177 | 13850 | 0.1056 | - | | 0.5196 | 13900 | 0.0825 | - | | 0.5215 | 13950 | 0.0741 | - | | 0.5233 | 14000 | 0.0425 | - | | 0.5252 | 14050 | 0.051 | - | | 0.5271 | 14100 | 0.0852 | - | | 0.5289 | 14150 | 0.0454 | - | | 0.5308 | 14200 | 0.0902 | - | | 0.5327 | 14250 | 0.0863 | - | | 0.5345 | 14300 | 0.0717 | - | | 0.5364 | 14350 | 0.1116 | - | | 0.5383 | 14400 | 0.0915 | - | | 0.5401 | 14450 | 0.0681 | - | | 0.5420 | 14500 | 0.0559 | - | | 0.5439 | 14550 | 0.063 | - | | 0.5458 | 14600 | 0.0856 | - | | 0.5476 | 14650 | 0.0661 | - | | 0.5495 | 14700 | 0.1111 | - | | 0.5514 | 14750 | 0.0983 | - | | 0.5532 | 14800 | 0.0885 | - | | 0.5551 | 14850 | 0.0612 | - | | 0.5570 | 14900 | 0.0764 | - | | 0.5588 | 14950 | 0.0693 | - | | 0.5607 | 15000 | 0.0839 | - | | 0.5626 | 15050 | 0.0872 | - | | 0.5644 | 15100 | 0.1113 | - | | 0.5663 | 15150 | 0.0576 | - | | 0.5682 | 15200 | 0.0645 | - | | 0.5701 | 15250 | 0.0471 | - | | 0.5719 | 15300 | 0.0376 | - | | 0.5738 | 15350 | 0.0798 | - | | 0.5757 | 15400 | 0.0996 | - | | 0.5775 | 15450 | 0.0497 | - | | 0.5794 | 15500 | 0.0579 | - | | 0.5813 | 15550 | 0.066 | - | | 0.5831 | 15600 | 0.1259 | - | | 0.5850 | 15650 | 0.0936 | - | | 0.5869 | 15700 | 0.0954 | - | | 0.5887 | 15750 | 0.0543 | - | | 0.5906 | 15800 | 0.0268 | - | | 0.5925 | 15850 | 0.0362 | - | | 0.5943 | 15900 | 0.0635 | - | | 0.5962 | 15950 | 0.0497 | - | | 0.5981 | 16000 | 0.0808 | - | | 0.6000 | 16050 | 0.0759 | - | | 0.6018 | 16100 | 0.0663 | - | | 0.6037 | 16150 | 0.0418 | - | | 0.6056 | 16200 | 0.0656 | - | | 0.6074 | 16250 | 0.053 | - | | 0.6093 | 16300 | 0.0763 | - | | 0.6112 | 16350 | 0.0663 | - | | 0.6130 | 16400 | 0.0651 | - | | 0.6149 | 16450 | 0.0774 | - | | 0.6168 | 16500 | 0.069 | - | | 0.6186 | 16550 | 0.0647 | - | | 0.6205 | 16600 | 0.0459 | - | | 0.6224 | 16650 | 0.0639 | - | | 0.6243 | 16700 | 0.0526 | - | | 0.6261 | 16750 | 0.0758 | - | | 0.6280 | 16800 | 0.04 | - | | 0.6299 | 16850 | 0.0758 | - | | 0.6317 | 16900 | 0.0421 | - | | 0.6336 | 16950 | 0.0557 | - | | 0.6355 | 17000 | 0.0733 | - | | 0.6373 | 17050 | 0.0467 | - | | 0.6392 | 17100 | 0.052 | - | | 0.6411 | 17150 | 0.1272 | - | | 0.6429 | 17200 | 0.081 | - | | 0.6448 | 17250 | 0.0396 | - | | 0.6467 | 17300 | 0.0494 | - | | 0.6485 | 17350 | 0.0934 | - | | 0.6504 | 17400 | 0.0745 | - | | 0.6523 | 17450 | 0.055 | - | | 0.6542 | 17500 | 0.065 | - | | 0.6560 | 17550 | 0.0407 | - | | 0.6579 | 17600 | 0.0409 | - | | 0.6598 | 17650 | 0.0317 | - | | 0.6616 | 17700 | 0.0433 | - | | 0.6635 | 17750 | 0.0512 | - | | 0.6654 | 17800 | 0.0731 | - | | 0.6672 | 17850 | 0.0296 | - | | 0.6691 | 17900 | 0.059 | - | | 0.6710 | 17950 | 0.0727 | - | | 0.6728 | 18000 | 0.0672 | - | | 0.6747 | 18050 | 0.0661 | - | | 0.6766 | 18100 | 0.0572 | - | | 0.6785 | 18150 | 0.0499 | - | | 0.6803 | 18200 | 0.0839 | - | | 0.6822 | 18250 | 0.054 | - | | 0.6841 | 18300 | 0.0754 | - | | 0.6859 | 18350 | 0.1177 | - | | 0.6878 | 18400 | 0.0772 | - | | 0.6897 | 18450 | 0.063 | - | | 0.6915 | 18500 | 0.0705 | - | | 0.6934 | 18550 | 0.0653 | - | | 0.6953 | 18600 | 0.085 | - | | 0.6971 | 18650 | 0.0668 | - | | 0.6990 | 18700 | 0.0788 | - | | 0.7009 | 18750 | 0.0673 | - | | 0.7028 | 18800 | 0.0606 | - | | 0.7046 | 18850 | 0.0553 | - | | 0.7065 | 18900 | 0.0435 | - | | 0.7084 | 18950 | 0.071 | - | | 0.7102 | 19000 | 0.0679 | - | | 0.7121 | 19050 | 0.0632 | - | | 0.7140 | 19100 | 0.0651 | - | | 0.7158 | 19150 | 0.092 | - | | 0.7177 | 19200 | 0.0626 | - | | 0.7196 | 19250 | 0.0643 | - | | 0.7214 | 19300 | 0.0242 | - | | 0.7233 | 19350 | 0.0632 | - | | 0.7252 | 19400 | 0.0638 | - | | 0.7270 | 19450 | 0.0543 | - | | 0.7289 | 19500 | 0.0312 | - | | 0.7308 | 19550 | 0.1124 | - | | 0.7327 | 19600 | 0.0432 | - | | 0.7345 | 19650 | 0.0868 | - | | 0.7364 | 19700 | 0.0493 | - | | 0.7383 | 19750 | 0.0301 | - | | 0.7401 | 19800 | 0.048 | - | | 0.7420 | 19850 | 0.0594 | - | | 0.7439 | 19900 | 0.0391 | - | | 0.7457 | 19950 | 0.0523 | - | | 0.7476 | 20000 | 0.0951 | - | | 0.7495 | 20050 | 0.0954 | - | | 0.7513 | 20100 | 0.0716 | - | | 0.7532 | 20150 | 0.0366 | - | | 0.7551 | 20200 | 0.0751 | - | | 0.7570 | 20250 | 0.0516 | - | | 0.7588 | 20300 | 0.1157 | - | | 0.7607 | 20350 | 0.0645 | - | | 0.7626 | 20400 | 0.065 | - | | 0.7644 | 20450 | 0.0469 | - | | 0.7663 | 20500 | 0.0943 | - | | 0.7682 | 20550 | 0.0884 | - | | 0.7700 | 20600 | 0.106 | - | | 0.7719 | 20650 | 0.0783 | - | | 0.7738 | 20700 | 0.0382 | - | | 0.7756 | 20750 | 0.0686 | - | | 0.7775 | 20800 | 0.0689 | - | | 0.7794 | 20850 | 0.0721 | - | | 0.7812 | 20900 | 0.0652 | - | | 0.7831 | 20950 | 0.0994 | - | | 0.7850 | 21000 | 0.0713 | - | | 0.7869 | 21050 | 0.0612 | - | | 0.7887 | 21100 | 0.0664 | - | | 0.7906 | 21150 | 0.0514 | - | | 0.7925 | 21200 | 0.0801 | - | | 0.7943 | 21250 | 0.0469 | - | | 0.7962 | 21300 | 0.0976 | - | | 0.7981 | 21350 | 0.0998 | - | | 0.7999 | 21400 | 0.0495 | - | | 0.8018 | 21450 | 0.0625 | - | | 0.8037 | 21500 | 0.0775 | - | | 0.8055 | 21550 | 0.049 | - | | 0.8074 | 21600 | 0.0816 | - | | 0.8093 | 21650 | 0.0644 | - | | 0.8112 | 21700 | 0.071 | - | | 0.8130 | 21750 | 0.052 | - | | 0.8149 | 21800 | 0.0267 | - | | 0.8168 | 21850 | 0.0598 | - | | 0.8186 | 21900 | 0.0402 | - | | 0.8205 | 21950 | 0.0525 | - | | 0.8224 | 22000 | 0.0745 | - | | 0.8242 | 22050 | 0.061 | - | | 0.8261 | 22100 | 0.0623 | - | | 0.8280 | 22150 | 0.0823 | - | | 0.8298 | 22200 | 0.0413 | - | | 0.8317 | 22250 | 0.0679 | - | | 0.8336 | 22300 | 0.0684 | - | | 0.8355 | 22350 | 0.0372 | - | | 0.8373 | 22400 | 0.0754 | - | | 0.8392 | 22450 | 0.0714 | - | | 0.8411 | 22500 | 0.089 | - | | 0.8429 | 22550 | 0.0614 | - | | 0.8448 | 22600 | 0.0584 | - | | 0.8467 | 22650 | 0.0978 | - | | 0.8485 | 22700 | 0.0639 | - | | 0.8504 | 22750 | 0.0849 | - | | 0.8523 | 22800 | 0.069 | - | | 0.8541 | 22850 | 0.0533 | - | | 0.8560 | 22900 | 0.0655 | - | | 0.8579 | 22950 | 0.0516 | - | | 0.8597 | 23000 | 0.0684 | - | | 0.8616 | 23050 | 0.0471 | - | | 0.8635 | 23100 | 0.0514 | - | | 0.8654 | 23150 | 0.0665 | - | | 0.8672 | 23200 | 0.0475 | - | | 0.8691 | 23250 | 0.0915 | - | | 0.8710 | 23300 | 0.0757 | - | | 0.8728 | 23350 | 0.0549 | - | | 0.8747 | 23400 | 0.0468 | - | | 0.8766 | 23450 | 0.0961 | - | | 0.8784 | 23500 | 0.0659 | - | | 0.8803 | 23550 | 0.0544 | - | | 0.8822 | 23600 | 0.1077 | - | | 0.8840 | 23650 | 0.0527 | - | | 0.8859 | 23700 | 0.0617 | - | | 0.8878 | 23750 | 0.0547 | - | | 0.8897 | 23800 | 0.0336 | - | | 0.8915 | 23850 | 0.0567 | - | | 0.8934 | 23900 | 0.0601 | - | | 0.8953 | 23950 | 0.0577 | - | | 0.8971 | 24000 | 0.0884 | - | | 0.8990 | 24050 | 0.0614 | - | | 0.9009 | 24100 | 0.0382 | - | | 0.9027 | 24150 | 0.0506 | - | | 0.9046 | 24200 | 0.0341 | - | | 0.9065 | 24250 | 0.0534 | - | | 0.9083 | 24300 | 0.0814 | - | | 0.9102 | 24350 | 0.0874 | - | | 0.9121 | 24400 | 0.0621 | - | | 0.9140 | 24450 | 0.0793 | - | | 0.9158 | 24500 | 0.0831 | - | | 0.9177 | 24550 | 0.0564 | - | | 0.9196 | 24600 | 0.0487 | - | | 0.9214 | 24650 | 0.1 | - | | 0.9233 | 24700 | 0.0852 | - | | 0.9252 | 24750 | 0.054 | - | | 0.9270 | 24800 | 0.046 | - | | 0.9289 | 24850 | 0.0523 | - | | 0.9308 | 24900 | 0.0661 | - | | 0.9326 | 24950 | 0.0682 | - | | 0.9345 | 25000 | 0.0418 | - | | 0.9364 | 25050 | 0.0608 | - | | 0.9382 | 25100 | 0.0951 | - | | 0.9401 | 25150 | 0.052 | - | | 0.9420 | 25200 | 0.0464 | - | | 0.9439 | 25250 | 0.0874 | - | | 0.9457 | 25300 | 0.033 | - | | 0.9476 | 25350 | 0.0492 | - | | 0.9495 | 25400 | 0.0735 | - | | 0.9513 | 25450 | 0.0659 | - | | 0.9532 | 25500 | 0.0936 | - | | 0.9551 | 25550 | 0.085 | - | | 0.9569 | 25600 | 0.0607 | - | | 0.9588 | 25650 | 0.0646 | - | | 0.9607 | 25700 | 0.0835 | - | | 0.9625 | 25750 | 0.0641 | - | | 0.9644 | 25800 | 0.0603 | - | | 0.9663 | 25850 | 0.0857 | - | | 0.9682 | 25900 | 0.0605 | - | | 0.9700 | 25950 | 0.0614 | - | | 0.9719 | 26000 | 0.0617 | - | | 0.9738 | 26050 | 0.0639 | - | | 0.9756 | 26100 | 0.0502 | - | | 0.9775 | 26150 | 0.089 | - | | 0.9794 | 26200 | 0.0604 | - | | 0.9812 | 26250 | 0.0867 | - | | 0.9831 | 26300 | 0.0597 | - | | 0.9850 | 26350 | 0.0755 | - | | 0.9868 | 26400 | 0.0628 | - | | 0.9887 | 26450 | 0.0685 | - | | 0.9906 | 26500 | 0.0794 | - | | 0.9924 | 26550 | 0.0892 | - | | 0.9943 | 26600 | 0.0716 | - | | 0.9962 | 26650 | 0.0397 | - | | 0.9981 | 26700 | 0.0933 | - | | 0.9999 | 26750 | 0.0663 | - | ### Framework Versions - Python: 3.10.6 - SetFit: 1.0.3 - Sentence Transformers: 2.3.1 - Transformers: 4.35.2 - PyTorch: 2.2.0 - Datasets: 2.21.0 - Tokenizers: 0.15.1 ## Citation ### BibTeX ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```