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Add SetFit model

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README.md ADDED
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+ ---
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+ library_name: setfit
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+ tags:
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+ - setfit
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+ - sentence-transformers
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+ - text-classification
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+ - generated_from_setfit_trainer
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+ metrics:
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+ - accuracy
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+ widget:
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+ - text: Buses are more simple - you just buy a ticket .
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+ - text: As citizens of village , we totally care about environment of our village
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+ .
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+ - text: So , finally I suggest that it would be a great idea to combine the different
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+ types of activities , both popular and the newest .
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+ - text: Had 12 years old .
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+ - text: On the other hand , I have the theoretical knowledge to use new the technologies
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+ this great project requires .
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+ pipeline_tag: text-classification
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+ inference: true
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+ base_model: sentence-transformers/paraphrase-mpnet-base-v2
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+ model-index:
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+ - name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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+ results:
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+ - task:
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+ type: text-classification
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+ name: Text Classification
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+ dataset:
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+ name: Unknown
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+ type: unknown
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+ split: test
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+ metrics:
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+ - type: accuracy
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+ value: 0.13152173913043477
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+ name: Accuracy
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+ ---
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+
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+ # SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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+
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+ 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 [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance is used for classification.
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+
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+ The model has been trained using an efficient few-shot learning technique that involves:
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+
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+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
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+
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+ ## Model Details
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+
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+ ### Model Description
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+ - **Model Type:** SetFit
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+ - **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
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+ - **Classification head:** a [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance
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+ - **Maximum Sequence Length:** 512 tokens
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+ - **Number of Classes:** 8 classes
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+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
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+ <!-- - **Language:** Unknown -->
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+ <!-- - **License:** Unknown -->
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+
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+ ### Model Sources
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+
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+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
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+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
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+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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+
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+ ### Model Labels
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+ | Label | Examples |
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+ |:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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+ | 7 | <ul><li>"When I 've had a very bad and stressful day I can relax doing karate , because It 's the kind of sport that it is n't very hard ."</li><li>"Also , you 'll meet friendly people who usually ask to you something to be friends and change your telephone number ."</li><li>'When I have spare time , I often gather my friends to watch basketball match on television .'</li></ul> |
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+ | 4 | <ul><li>"stop shouting . do n't shout ."</li><li>'Yours Sincerely .'</li><li>'Something that they don know was that the whole thing was a movie !'</li></ul> |
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+ | 1 | <ul><li>'She stay sleeping in the bed and doing nothing all day .'</li><li>'People collects trash of their house and await the trash truck that carried the trash to a landfill located outside the village .'</li><li>"Travelling by car is n't so much more convenient unless it is so much more comfortable , but actually we do n't think about the contamination in our planet ."</li></ul> |
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+ | 6 | <ul><li>'When the concert finished , we went to cloakroom to get signatures from musicians .'</li><li>'We have solar panels and a place to make compost at the last garden , with worms who eat and degrade all the organic waste of the school .'</li><li>'The aim of this report is to give you my personal point of view of the course I did in your branch in Madrid last month .'</li></ul> |
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+ | 5 | <ul><li>'You can also bought a lot of gifts like key chains , statue , or what else memories to be made before returning to Malaysia .'</li><li>'I always said that I passed that test and I was sure of that .'</li><li>'In addition , to decrease the risk of negative comments or posts , Facebook and Twitter would improve their futures to solve the less personal privacy problem .'</li></ul> |
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+ | 2 | <ul><li>'They were not only really clever people but also excellent co - workers .'</li><li>'On balance , learning foreign languages is very positive on different aspect , so if you have the positivity of learning a new language do it , because it will bring you many benefits .'</li><li>'In many years of work I have honed my skills in managing non - standard situations , analyzing the problem , finding and implementing practical and easy solutions .'</li></ul> |
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+ | 0 | <ul><li>'It is very funny .'</li><li>'In China , English is took to be a foreign language which many students choose to learn .'</li><li>'We also value that they have specialised studies in Cloud technology , and hosting management .'</li></ul> |
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+ | 3 | <ul><li>"Usually there are generation problems , sons do n't understand parents and vicecersa , but dialoging and listening emotions and facts , everyone can have another point of view ."</li><li>'the two boys heard that he was planing to steal some money and kill people so the boys start their adventure on stoping Injuin Joe ...'</li><li>'As an example , if you are able to get alone with your travel companion could enjoy each moment of the trip , exchange some pictures , eat together , and visit places with common interest such as museums or malls .'</li></ul> |
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+
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+ ## Evaluation
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+
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+ ### Metrics
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+ | Label | Accuracy |
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+ |:--------|:---------|
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+ | **all** | 0.1315 |
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+
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+ ## Uses
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+
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+ ### Direct Use for Inference
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+
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+ First install the SetFit library:
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+
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+ ```bash
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+ pip install setfit
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+ ```
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+
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+ Then you can load this model and run inference.
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+
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+ ```python
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+ from setfit import SetFitModel
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+
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+ # Download from the 🤗 Hub
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+ model = SetFitModel.from_pretrained("HelgeKn/BEA2019-multi-class-4")
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+ # Run inference
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+ preds = model("Had 12 years old .")
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+ ```
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+
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+ <!--
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+ ### Downstream Use
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+
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+ *List how someone could finetune this model on their own dataset.*
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+ -->
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+
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+ <!--
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+ ### Out-of-Scope Use
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+
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+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
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+ -->
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+
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+ <!--
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+ ## Bias, Risks and Limitations
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+
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+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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+ -->
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+
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+ <!--
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+ ### Recommendations
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+
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+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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+ -->
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+
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+ ## Training Details
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+
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+ ### Training Set Metrics
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+ | Training set | Min | Median | Max |
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+ |:-------------|:----|:--------|:----|
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+ | Word count | 3 | 19.1562 | 42 |
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+
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+ | Label | Training Sample Count |
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+ |:------|:----------------------|
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+ | 0 | 4 |
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+ | 1 | 4 |
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+ | 2 | 4 |
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+ | 3 | 4 |
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+ | 4 | 4 |
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+ | 5 | 4 |
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+ | 6 | 4 |
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+ | 7 | 4 |
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+
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+ ### Training Hyperparameters
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+ - batch_size: (16, 16)
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+ - num_epochs: (2, 2)
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+ - max_steps: -1
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+ - sampling_strategy: oversampling
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+ - num_iterations: 20
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+ - body_learning_rate: (2e-05, 2e-05)
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+ - head_learning_rate: 2e-05
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+ - loss: CosineSimilarityLoss
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+ - distance_metric: cosine_distance
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+ - margin: 0.25
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+ - end_to_end: False
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+ - use_amp: False
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+ - warmup_proportion: 0.1
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+ - seed: 42
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+ - eval_max_steps: -1
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+ - load_best_model_at_end: False
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+
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+ ### Training Results
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+ | Epoch | Step | Training Loss | Validation Loss |
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+ |:------:|:----:|:-------------:|:---------------:|
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+ | 0.0125 | 1 | 0.1886 | - |
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+ | 0.625 | 50 | 0.0778 | - |
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+ | 1.25 | 100 | 0.0194 | - |
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+ | 1.875 | 150 | 0.0069 | - |
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+
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+ ### Framework Versions
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+ - Python: 3.9.13
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+ - SetFit: 1.0.1
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+ - Sentence Transformers: 2.2.2
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+ - Transformers: 4.36.0
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+ - PyTorch: 2.1.1+cpu
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+ - Datasets: 2.15.0
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+ - Tokenizers: 0.15.0
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+
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+ ## Citation
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+
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+ ### BibTeX
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+ ```bibtex
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+ @article{https://doi.org/10.48550/arxiv.2209.11055,
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+ doi = {10.48550/ARXIV.2209.11055},
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+ url = {https://arxiv.org/abs/2209.11055},
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+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
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+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
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+ title = {Efficient Few-Shot Learning Without Prompts},
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+ publisher = {arXiv},
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+ year = {2022},
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+ copyright = {Creative Commons Attribution 4.0 International}
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+ }
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+ ```
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+
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+ <!--
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+ ## Glossary
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+
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+ *Clearly define terms in order to be accessible across audiences.*
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+ -->
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+
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+ <!--
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+ ## Model Card Authors
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+
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+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
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+ -->
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+
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+ <!--
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+ ## Model Card Contact
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+
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+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
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+ -->
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