--- library_name: setfit tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer metrics: - accuracy widget: - text: In the context of mathematical economics, the paper demonstrates that the use of martingales and stochastic integrals in continuous trading can lead to both profitable and unprofitable reactions to market movements. - text: Gold catalysts prepared by coprecipitation with a particle size below 10 nm were selected for the study. - text: This study calculates radiative forcing by long-lived greenhouse gases using the AER radiative transfer models in the atmospheric sciences. - text: This chapter focuses on the antimicrobial and phytochemical investigation of 45 Indian medicinal plants and their potential in combating multi-drug resistant human pathogens within the realm of traditional medicine. - text: The synthesis and application of smart biocompatible materials based on poly(oligo(ethylene glycol) (meth)acrylates) have gained significant attention in the field of polymer chemistry due to their potential in biomedical applications. pipeline_tag: text-classification inference: true base_model: kaisugi/scitoricsbert model-index: - name: SetFit with kaisugi/scitoricsbert results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 0.7970873786407767 name: Accuracy --- # SetFit with kaisugi/scitoricsbert This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [kaisugi/scitoricsbert](https://huggingface.co/kaisugi/scitoricsbert) 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. 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:** [kaisugi/scitoricsbert](https://huggingface.co/kaisugi/scitoricsbert) - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - **Maximum Sequence Length:** 512 tokens - **Number of Classes:** 103 classes ### 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) ### Model Labels | Label | Examples | |:-------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Acknowledging limitation(s) whilst stating a finding or contribution | | | Advising cautious interpretation of the findings | | | Commenting on the findings | | | Commenting on the strengths of the current study | | | Comparing the result: contradicting previous findings | | | Comparing the result: supporting previous findings | | | Contrasting sources with ‘however’ for emphasis | | | Describing previously used methods | | | Describing questionnaire design | | | Describing the characteristics of the participants | | | Describing the limitations of the current study | | | Describing the process: adverbs of manner | | | Describing the process: expressing purpose with for | | | Describing the process: infinitive of purpose | | | Describing the process: sequence words | | | Describing the process: statistical procedures | | | Describing the process: typical verbs in the passive form | | | Describing the process: using + instrument | | | Describing the research design and the methods used | | | Describing what other writers do in their published work | | | Detailing specific limitations | | | Establishing the importance of the topic for the discipline | | | Establishing the importance of the topic for the discipline: time frame given | | | Establishing the importance of the topic for the world or society | | | Establishing the importance of the topic for the world or society: time frame given | | | Establising the importance of the topic as a problem to be addressed | | | Explaining keywords (also refer to Defining Terms) | | | Explaining the provenance of articles for review | | | Explaining the provenance of the participants | | | Explaining the significance of the current study | | | Explaining the significance of the findings or contribution of the study | | | General comments on the relevant literature | | | General reference to previous research or scholarship: highlighting negative outcomes | | | Giving reasons for personal interest in the research (sometimes found in the humanities, and the applied human sciences) | | | Giving reasons why a particular method was adopted | | | Giving reasons why a particular method was rejected | | | Highlighting inadequacies or weaknesses of previous studies (also refer to Being Critical) | | | Highlighting interesting or surprising results | | | Highlighting significant data in a table or chart | | | Identifying a controversy within the field of study | | | Identifying a knowledge gap in the field of study | | | Implications and/or recommendations for practice or policy | | | Indicating an expected outcome | | | Indicating an unexpected outcome | | | Indicating criteria for selection or inclusion in the study | | | Indicating methodological problems or limitations | | | Indicating missing, weak, or contradictory evidence | | | Indicating the methodology for the current research | | | Indicating the use of an established method | | | Introducing the limitations of the current study | | | Making recommendations for further research work | | | Noting implications of the findings | | | Noting the lack of or paucity of previous research | | | Offering an explanation for the findings | | | Outlining the structure of a short paper | | | Outlining the structure of a thesis or dissertation | | | Pointing out interesting or important findings | | | Previewing a chapter | | | Previous research: A historic perspective | | | Previous research: Approaches taken | | | Previous research: What has been established or proposed | | | Previous research: area investigated as the sentence object | | | Previous research: area investigated as the sentence subject | | | Previous research: highlighting negative outcomes | | | Providing background information: reference to the literature | | | Providing background information: reference to the purpose of the study | | | Reference to previous research: important studies | | | Referring back to the purpose of the paper or study | | | Referring back to the research aims or procedures | | | Referring to a single investigation in the past: investigation prominent | | | Referring to a single investigation in the past: researcher prominent | | | Referring to another writer’s idea(s) or position | | | Referring to data in a table or chart | | | Referring to important texts in the area of interest | | | Referring to previous work to establish what is already known | | | Referring to secondary sources | | | Referring to the literature to justify a method or approach | | | Reporting positive and negative reactions | | | Restating a result or one of several results | | | Setting out the research questions or hypotheses | | | Some ways of introducing quotations | | | Stating a negative result | | | Stating a positive result | | | Stating purpose of the current research with reference to gaps or issues in the literature | | | Stating the aims of the current research (note frequent use of past tense) | | | Stating the focus, aim, or argument of a short paper | | | Stating the purpose of the thesis, dissertation, or research article (note use of present tense) | | | Stating what is currently known about the topic | | | Suggesting general hypotheses | | | Suggesting implications for what is already known | | | Suggestions for future work | | | Summarising the literature review | | | Summarising the main research findings | | | Summarising the results section | | | Summarising the studies reviewed | | | Surveys and interviews: Introducing excerpts from interview data | | | Surveys and interviews: Reporting participants’ views | | | Surveys and interviews: Reporting proportions | | | Surveys and interviews: Reporting response rates | | | Surveys and interviews: Reporting themes | | | Synthesising sources: contrasting evidence or ideas | | | Synthesising sources: supporting evidence or ideas | | | Transition: moving to the next result | | ## Evaluation ### Metrics | Label | Accuracy | |:--------|:---------| | **all** | 0.7971 | ## 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("Corran/SciGenSetfit5") # Run inference preds = model("Gold catalysts prepared by coprecipitation with a particle size below 10 nm were selected for the study.") ``` ## Training Details ### Training Set Metrics | Training set | Min | Median | Max | |:-------------|:----|:--------|:----| | Word count | 5 | 28.3208 | 71 | | Label | Training Sample Count | |:-------------------------------------------------------------------------------------------------------------------------|:----------------------| | Acknowledging limitation(s) whilst stating a finding or contribution | 200 | | Advising cautious interpretation of the findings | 200 | | Commenting on the findings | 200 | | Commenting on the strengths of the current study | 200 | | Comparing the result: contradicting previous findings | 200 | | Comparing the result: supporting previous findings | 200 | | Contrasting sources with ‘however’ for emphasis | 200 | | Describing previously used methods | 200 | | Describing questionnaire design | 200 | | Describing the characteristics of the participants | 200 | | Describing the limitations of the current study | 200 | | Describing the process: adverbs of manner | 200 | | Describing the process: expressing purpose with for | 200 | | Describing the process: infinitive of purpose | 200 | | Describing the process: sequence words | 200 | | Describing the process: statistical procedures | 200 | | Describing the process: typical verbs in the passive form | 200 | | Describing the process: using + instrument | 200 | | Describing the research design and the methods used | 200 | | Describing what other writers do in their published work | 200 | | Detailing specific limitations | 200 | | Establishing the importance of the topic for the discipline | 200 | | Establishing the importance of the topic for the discipline: time frame given | 200 | | Establishing the importance of the topic for the world or society | 200 | | Establishing the importance of the topic for the world or society: time frame given | 200 | | Establising the importance of the topic as a problem to be addressed | 200 | | Explaining keywords (also refer to Defining Terms) | 200 | | Explaining the provenance of articles for review | 200 | | Explaining the provenance of the participants | 200 | | Explaining the significance of the current study | 200 | | Explaining the significance of the findings or contribution of the study | 200 | | General comments on the relevant literature | 200 | | General reference to previous research or scholarship: highlighting negative outcomes | 200 | | Giving reasons for personal interest in the research (sometimes found in the humanities, and the applied human sciences) | 200 | | Giving reasons why a particular method was adopted | 200 | | Giving reasons why a particular method was rejected | 200 | | Highlighting inadequacies or weaknesses of previous studies (also refer to Being Critical) | 200 | | Highlighting interesting or surprising results | 200 | | Highlighting significant data in a table or chart | 200 | | Identifying a controversy within the field of study | 200 | | Identifying a knowledge gap in the field of study | 200 | | Implications and/or recommendations for practice or policy | 200 | | Indicating an expected outcome | 200 | | Indicating an unexpected outcome | 200 | | Indicating criteria for selection or inclusion in the study | 200 | | Indicating methodological problems or limitations | 200 | | Indicating missing, weak, or contradictory evidence | 200 | | Indicating the methodology for the current research | 200 | | Indicating the use of an established method | 200 | | Introducing the limitations of the current study | 155 | | Making recommendations for further research work | 200 | | Noting implications of the findings | 200 | | Noting the lack of or paucity of previous research | 200 | | Offering an explanation for the findings | 200 | | Outlining the structure of a short paper | 200 | | Outlining the structure of a thesis or dissertation | 200 | | Pointing out interesting or important findings | 200 | | Previewing a chapter | 200 | | Previous research: A historic perspective | 200 | | Previous research: Approaches taken | 200 | | Previous research: What has been established or proposed | 200 | | Previous research: area investigated as the sentence object | 200 | | Previous research: area investigated as the sentence subject | 200 | | Previous research: highlighting negative outcomes | 200 | | Providing background information: reference to the literature | 200 | | Providing background information: reference to the purpose of the study | 200 | | Reference to previous research: important studies | 200 | | Referring back to the purpose of the paper or study | 200 | | Referring back to the research aims or procedures | 200 | | Referring to a single investigation in the past: investigation prominent | 200 | | Referring to a single investigation in the past: researcher prominent | 200 | | Referring to another writer’s idea(s) or position | 200 | | Referring to data in a table or chart | 200 | | Referring to important texts in the area of interest | 200 | | Referring to previous work to establish what is already known | 200 | | Referring to secondary sources | 200 | | Referring to the literature to justify a method or approach | 200 | | Reporting positive and negative reactions | 200 | | Restating a result or one of several results | 200 | | Setting out the research questions or hypotheses | 200 | | Some ways of introducing quotations | 200 | | Stating a negative result | 200 | | Stating a positive result | 200 | | Stating purpose of the current research with reference to gaps or issues in the literature | 200 | | Stating the aims of the current research (note frequent use of past tense) | 200 | | Stating the focus, aim, or argument of a short paper | 200 | | Stating the purpose of the thesis, dissertation, or research article (note use of present tense) | 200 | | Stating what is currently known about the topic | 200 | | Suggesting general hypotheses | 200 | | Suggesting implications for what is already known | 200 | | Suggestions for future work | 200 | | Summarising the literature review | 200 | | Summarising the main research findings | 200 | | Summarising the results section | 200 | | Summarising the studies reviewed | 200 | | Surveys and interviews: Introducing excerpts from interview data | 200 | | Surveys and interviews: Reporting participants’ views | 200 | | Surveys and interviews: Reporting proportions | 200 | | Surveys and interviews: Reporting response rates | 200 | | Surveys and interviews: Reporting themes | 200 | | Synthesising sources: contrasting evidence or ideas | 200 | | Synthesising sources: supporting evidence or ideas | 200 | | Transition: moving to the next result | 200 | ### Training Hyperparameters - batch_size: (64, 64) - num_epochs: (1, 1) - max_steps: -1 - sampling_strategy: oversampling - num_iterations: 20 - 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 | |:------:|:-----:|:-------------:|:---------------:| | 0.0001 | 1 | 0.232 | - | | 0.0039 | 50 | 0.2466 | - | | 0.0078 | 100 | 0.2045 | - | | 0.0117 | 150 | 0.1845 | - | | 0.0156 | 200 | 0.1568 | - | | 0.0195 | 250 | 0.1452 | - | | 0.0234 | 300 | 0.1208 | - | | 0.0272 | 350 | 0.1628 | - | | 0.0311 | 400 | 0.1529 | - | | 0.0350 | 450 | 0.0884 | - | | 0.0389 | 500 | 0.1394 | - | | 0.0428 | 550 | 0.1458 | - | | 0.0467 | 600 | 0.089 | - | | 0.0506 | 650 | 0.1297 | - | | 0.0545 | 700 | 0.0981 | - | | 0.0584 | 750 | 0.1283 | - | | 0.0623 | 800 | 0.1304 | - | | 0.0662 | 850 | 0.097 | - | | 0.0701 | 900 | 0.1432 | - | | 0.0739 | 950 | 0.1195 | - | | 0.0778 | 1000 | 0.0746 | - | | 0.0817 | 1050 | 0.1491 | - | | 0.0856 | 1100 | 0.0956 | - | | 0.0895 | 1150 | 0.1033 | - | | 0.0934 | 1200 | 0.0957 | - | | 0.0973 | 1250 | 0.0996 | - | | 0.1012 | 1300 | 0.064 | - | | 0.1051 | 1350 | 0.0898 | - | | 0.1090 | 1400 | 0.074 | - | | 0.1129 | 1450 | 0.0964 | - | | 0.1168 | 1500 | 0.1135 | - | | 0.1207 | 1550 | 0.1174 | - | | 0.1245 | 1600 | 0.0885 | - | | 0.1284 | 1650 | 0.112 | - | | 0.1323 | 1700 | 0.0994 | - | | 0.1362 | 1750 | 0.0889 | - | | 0.1401 | 1800 | 0.0712 | - | | 0.1440 | 1850 | 0.0919 | - | | 0.1479 | 1900 | 0.0727 | - | | 0.1518 | 1950 | 0.0668 | - | | 0.1557 | 2000 | 0.0622 | - | | 0.1596 | 2050 | 0.0613 | - | | 0.1635 | 2100 | 0.0803 | - | | 0.1674 | 2150 | 0.1143 | - | | 0.1712 | 2200 | 0.0945 | - | | 0.1751 | 2250 | 0.0926 | - | | 0.1790 | 2300 | 0.0797 | - | | 0.1829 | 2350 | 0.0668 | - | | 0.1868 | 2400 | 0.0771 | - | | 0.1907 | 2450 | 0.0696 | - | | 0.1946 | 2500 | 0.0743 | - | | 0.1985 | 2550 | 0.0763 | - | | 0.2024 | 2600 | 0.0864 | - | | 0.2063 | 2650 | 0.0953 | - | | 0.2102 | 2700 | 0.0534 | - | | 0.2141 | 2750 | 0.0571 | - | | 0.2179 | 2800 | 0.0554 | - | | 0.2218 | 2850 | 0.0706 | - | | 0.2257 | 2900 | 0.0894 | - | | 0.2296 | 2950 | 0.0322 | - | | 0.2335 | 3000 | 0.0709 | - | | 0.2374 | 3050 | 0.066 | - | | 0.2413 | 3100 | 0.0799 | - | | 0.2452 | 3150 | 0.0502 | - | | 0.2491 | 3200 | 0.0742 | - | | 0.2530 | 3250 | 0.0562 | - | | 0.2569 | 3300 | 0.0518 | - | | 0.2608 | 3350 | 0.062 | - | | 0.2647 | 3400 | 0.0431 | - | | 0.2685 | 3450 | 0.0295 | - | | 0.2724 | 3500 | 0.05 | - | | 0.2763 | 3550 | 0.0523 | - | | 0.2802 | 3600 | 0.0507 | - | | 0.2841 | 3650 | 0.0669 | - | | 0.2880 | 3700 | 0.0558 | - | | 0.2919 | 3750 | 0.0676 | - | | 0.2958 | 3800 | 0.0357 | - | | 0.2997 | 3850 | 0.0591 | - | | 0.3036 | 3900 | 0.0676 | - | | 0.3075 | 3950 | 0.0596 | - | | 0.3114 | 4000 | 0.0407 | - | | 0.3152 | 4050 | 0.0392 | - | | 0.3191 | 4100 | 0.0257 | - | | 0.3230 | 4150 | 0.046 | - | | 0.3269 | 4200 | 0.0488 | - | | 0.3308 | 4250 | 0.0978 | - | | 0.3347 | 4300 | 0.0424 | - | | 0.3386 | 4350 | 0.0368 | - | | 0.3425 | 4400 | 0.0304 | - | | 0.3464 | 4450 | 0.0274 | - | | 0.3503 | 4500 | 0.0511 | - | | 0.3542 | 4550 | 0.0373 | - | | 0.3581 | 4600 | 0.0411 | - | | 0.3620 | 4650 | 0.0413 | - | | 0.3658 | 4700 | 0.0393 | - | | 0.3697 | 4750 | 0.0447 | - | | 0.3736 | 4800 | 0.0406 | - | | 0.3775 | 4850 | 0.0151 | - | | 0.3814 | 4900 | 0.0263 | - | | 0.3853 | 4950 | 0.0525 | - | | 0.3892 | 5000 | 0.0736 | - | | 0.3931 | 5050 | 0.1025 | - | | 0.3970 | 5100 | 0.0307 | - | | 0.4009 | 5150 | 0.0562 | - | | 0.4048 | 5200 | 0.0783 | - | | 0.4087 | 5250 | 0.0449 | - | | 0.4125 | 5300 | 0.043 | - | | 0.4164 | 5350 | 0.063 | - | | 0.4203 | 5400 | 0.0258 | - | | 0.4242 | 5450 | 0.0181 | - | | 0.4281 | 5500 | 0.0546 | - | | 0.4320 | 5550 | 0.0455 | - | | 0.4359 | 5600 | 0.0622 | - | | 0.4398 | 5650 | 0.0467 | - | | 0.4437 | 5700 | 0.0333 | - | | 0.4476 | 5750 | 0.0352 | - | | 0.4515 | 5800 | 0.0222 | - | | 0.4554 | 5850 | 0.0725 | - | | 0.4593 | 5900 | 0.0503 | - | | 0.4631 | 5950 | 0.0425 | - | | 0.4670 | 6000 | 0.018 | - | | 0.4709 | 6050 | 0.0343 | - | | 0.4748 | 6100 | 0.0293 | - | | 0.4787 | 6150 | 0.022 | - | | 0.4826 | 6200 | 0.0415 | - | | 0.4865 | 6250 | 0.0472 | - | | 0.4904 | 6300 | 0.0405 | - | | 0.4943 | 6350 | 0.0173 | - | | 0.4982 | 6400 | 0.0584 | - | | 0.5021 | 6450 | 0.0447 | - | | 0.5060 | 6500 | 0.0307 | - | | 0.5098 | 6550 | 0.0207 | - | | 0.5137 | 6600 | 0.037 | - | | 0.5176 | 6650 | 0.0347 | - | | 0.5215 | 6700 | 0.0498 | - | | 0.5254 | 6750 | 0.0348 | - | | 0.5293 | 6800 | 0.0302 | - | | 0.5332 | 6850 | 0.0481 | - | | 0.5371 | 6900 | 0.0407 | - | | 0.5410 | 6950 | 0.0249 | - | | 0.5449 | 7000 | 0.047 | - | | 0.5488 | 7050 | 0.0213 | - | | 0.5527 | 7100 | 0.0405 | - | | 0.5566 | 7150 | 0.0062 | - | | 0.5604 | 7200 | 0.0212 | - | | 0.5643 | 7250 | 0.0216 | - | | 0.5682 | 7300 | 0.0178 | - | | 0.5721 | 7350 | 0.0544 | - | | 0.5760 | 7400 | 0.0598 | - | | 0.5799 | 7450 | 0.0178 | - | | 0.5838 | 7500 | 0.0181 | - | | 0.5877 | 7550 | 0.052 | - | | 0.5916 | 7600 | 0.0332 | - | | 0.5955 | 7650 | 0.0734 | - | | 0.5994 | 7700 | 0.0362 | - | | 0.6033 | 7750 | 0.0112 | - | | 0.6071 | 7800 | 0.0221 | - | | 0.6110 | 7850 | 0.0552 | - | | 0.6149 | 7900 | 0.022 | - | | 0.6188 | 7950 | 0.0144 | - | | 0.6227 | 8000 | 0.0163 | - | | 0.6266 | 8050 | 0.0329 | - | | 0.6305 | 8100 | 0.0208 | - | | 0.6344 | 8150 | 0.0574 | - | | 0.6383 | 8200 | 0.0124 | - | | 0.6422 | 8250 | 0.0332 | - | | 0.6461 | 8300 | 0.0295 | - | | 0.6500 | 8350 | 0.0586 | - | | 0.6538 | 8400 | 0.0156 | - | | 0.6577 | 8450 | 0.0327 | - | | 0.6616 | 8500 | 0.0229 | - | | 0.6655 | 8550 | 0.0346 | - | | 0.6694 | 8600 | 0.0189 | - | | 0.6733 | 8650 | 0.0056 | - | | 0.6772 | 8700 | 0.0399 | - | | 0.6811 | 8750 | 0.0436 | - | | 0.6850 | 8800 | 0.0115 | - | | 0.6889 | 8850 | 0.0241 | - | | 0.6928 | 8900 | 0.0097 | - | | 0.6967 | 8950 | 0.0169 | - | | 0.7006 | 9000 | 0.055 | - | | 0.7044 | 9050 | 0.0317 | - | | 0.7083 | 9100 | 0.0119 | - | | 0.7122 | 9150 | 0.0055 | - | | 0.7161 | 9200 | 0.0126 | - | | 0.7200 | 9250 | 0.0198 | - | | 0.7239 | 9300 | 0.0338 | - | | 0.7278 | 9350 | 0.0481 | - | | 0.7317 | 9400 | 0.0227 | - | | 0.7356 | 9450 | 0.0143 | - | | 0.7395 | 9500 | 0.0232 | - | | 0.7434 | 9550 | 0.0251 | - | | 0.7473 | 9600 | 0.0078 | - | | 0.7511 | 9650 | 0.018 | - | | 0.7550 | 9700 | 0.055 | - | | 0.7589 | 9750 | 0.0512 | - | | 0.7628 | 9800 | 0.0073 | - | | 0.7667 | 9850 | 0.04 | - | | 0.7706 | 9900 | 0.0241 | - | | 0.7745 | 9950 | 0.0483 | - | | 0.7784 | 10000 | 0.0216 | - | | 0.7823 | 10050 | 0.0151 | - | | 0.7862 | 10100 | 0.018 | - | | 0.7901 | 10150 | 0.0347 | - | | 0.7940 | 10200 | 0.0223 | - | | 0.7979 | 10250 | 0.0261 | - | | 0.8017 | 10300 | 0.0317 | - | | 0.8056 | 10350 | 0.0331 | - | | 0.8095 | 10400 | 0.0296 | - | | 0.8134 | 10450 | 0.0488 | - | | 0.8173 | 10500 | 0.0383 | - | | 0.8212 | 10550 | 0.021 | - | | 0.8251 | 10600 | 0.0412 | - | | 0.8290 | 10650 | 0.0143 | - | | 0.8329 | 10700 | 0.0297 | - | | 0.8368 | 10750 | 0.0128 | - | | 0.8407 | 10800 | 0.0329 | - | | 0.8446 | 10850 | 0.0125 | - | | 0.8484 | 10900 | 0.0032 | - | | 0.8523 | 10950 | 0.0197 | - | | 0.8562 | 11000 | 0.0099 | - | | 0.8601 | 11050 | 0.0314 | - | | 0.8640 | 11100 | 0.0169 | - | | 0.8679 | 11150 | 0.0188 | - | | 0.8718 | 11200 | 0.0329 | - | | 0.8757 | 11250 | 0.0436 | - | | 0.8796 | 11300 | 0.0182 | - | | 0.8835 | 11350 | 0.0299 | - | | 0.8874 | 11400 | 0.018 | - | | 0.8913 | 11450 | 0.0091 | - | | 0.8952 | 11500 | 0.0334 | - | | 0.8990 | 11550 | 0.0034 | - | | 0.9029 | 11600 | 0.0213 | - | | 0.9068 | 11650 | 0.0339 | - | | 0.9107 | 11700 | 0.0474 | - | | 0.9146 | 11750 | 0.027 | - | | 0.9185 | 11800 | 0.0218 | - | | 0.9224 | 11850 | 0.0263 | - | | 0.9263 | 11900 | 0.0129 | - | | 0.9302 | 11950 | 0.0132 | - | | 0.9341 | 12000 | 0.0502 | - | | 0.9380 | 12050 | 0.0049 | - | | 0.9419 | 12100 | 0.0341 | - | | 0.9457 | 12150 | 0.0109 | - | | 0.9496 | 12200 | 0.007 | - | | 0.9535 | 12250 | 0.0127 | - | | 0.9574 | 12300 | 0.0275 | - | | 0.9613 | 12350 | 0.0031 | - | | 0.9652 | 12400 | 0.009 | - | | 0.9691 | 12450 | 0.0376 | - | | 0.9730 | 12500 | 0.0127 | - | | 0.9769 | 12550 | 0.0245 | - | | 0.9808 | 12600 | 0.0359 | - | | 0.9847 | 12650 | 0.0245 | - | | 0.9886 | 12700 | 0.0449 | - | | 0.9924 | 12750 | 0.0083 | - | | 0.9963 | 12800 | 0.0434 | - | ### Framework Versions - Python: 3.10.12 - SetFit: 1.0.3 - Sentence Transformers: 2.2.2 - Transformers: 4.35.2 - PyTorch: 2.1.0+cu121 - Datasets: 2.16.1 - Tokenizers: 0.15.0 ## 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} } ```