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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: I know you are searching for a flat to live for the whole next year .
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+ - text: Dear sir Dimara .
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+ - text: I have been doing Judo for the past 11 years with a lot of prizes .
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+ - text: my village is the place where I live so I am trying to keep its environment
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+ non - polluted and valid for life .
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+ - text: I learnt from Research that you can do everything in anytime in addition a
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+ little tired can change the life for the better .
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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: 0.175
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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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+ | 1 | <ul><li>'I consider that is more convenient to drive a car because you carry on more things in your own car than travelling by car .'</li><li>'In the last few years forensic biology has developed many aspects like better sensibility , robustness of results and less time required for analyze a sample , but what struck me most is how fast this change happens .'</li><li>"The car is n't the best way for for the transport , because it produce much pollution , however the public transport is better to do a journey ."</li></ul> |
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+ | 6 | <ul><li>'On the one hand travel by car are really much more convenient as give the chance to you to be independent .'</li><li>'When most people think about an important historical place in Italy , they think of Duomo , in Milano .'</li><li>'I like personality with childlike , so I like children .'</li></ul> |
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+ | 5 | <ul><li>'Yours sincerely ,'</li><li>'This practice is considered those activities that anyone can do without any kind of special preparation .'</li><li>'Secondly , the public vehicle route are more far than usual route .'</li></ul> |
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+ | 7 | <ul><li>'This conclusion become more prominent if we look into the data of the car companies and exponential growth in their sales figure and with low budget private cars in picture , scenario ddrastically changed in past 10 years'</li><li>'Recently I saw the thriller of mokingjay part 2 .'</li><li>"An example of that is the marriage of homosexual where some state admit this marriage , others do n't ."</li></ul> |
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+ | 3 | <ul><li>'After that , the sports day began formally .'</li><li>'In those years I lived the worst moments in my life .'</li><li>'On the one hand , in my country there are a lot of place to travel .'</li></ul> |
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+ | 2 | <ul><li>"Sharing houses or rooms have many advantages such as , cheap , safe , close to the university , and learn how to share everything with others . saving money and time will be more Obvious in university dormitories because monthly payments will be less than four times than hiring an apartment , and because it will be closer to the university , saving money and time is more efficient by reducing transportation 's costs"</li><li>'So , finally I suggest that it would be a great idea to combine the different types of activities , both popular and the newest .'</li><li>'Wszysycy residents of my village , they try to , so that our village was clear that pollute the environment as little as possible .'</li></ul> |
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+ | 4 | <ul><li>'During summer I love to go to the beach and having sunbathing with my friends other than getting fun with them playing volleyball or run inside the water of the sea !'</li><li>'Jose is the best song . he is singing and talking in the party .'</li><li>"She fell sleep again , didn't she ?"</li></ul> |
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+ | 0 | <ul><li>'I work for the same large company for 25 years , now is the time to change and find new job opportunities .'</li><li>'A problem which was caused by us , human beings , with their target of making money without thinking of the effects .'</li><li>'He was waiting 2 hours for her .'</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** | 0.175 |
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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-20")
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+ # Run inference
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+ preds = model("Dear sir Dimara .")
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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 | 22.0 | 82 |
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+
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+ | Label | Training Sample Count |
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+ |:------|:----------------------|
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+ | 0 | 20 |
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+ | 1 | 20 |
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+ | 2 | 20 |
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+ | 3 | 20 |
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+ | 4 | 20 |
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+ | 5 | 20 |
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+ | 6 | 20 |
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+ | 7 | 20 |
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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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+ | 0.0025 | 1 | 0.3724 | - |
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+ | 0.125 | 50 | 0.2732 | - |
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+ | 0.25 | 100 | 0.3001 | - |
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+ | 0.375 | 150 | 0.2525 | - |
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+ | 0.5 | 200 | 0.1934 | - |
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+ | 0.625 | 250 | 0.1164 | - |
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+ | 0.75 | 300 | 0.0874 | - |
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+ | 0.875 | 350 | 0.0624 | - |
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+ | 1.0 | 400 | 0.052 | - |
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+ | 1.125 | 450 | 0.0569 | - |
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+ | 1.25 | 500 | 0.0248 | - |
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+ | 1.375 | 550 | 0.0071 | - |
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+ | 1.5 | 600 | 0.0124 | - |
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+ | 1.625 | 650 | 0.0087 | - |
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+ | 1.75 | 700 | 0.0086 | - |
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+ | 1.875 | 750 | 0.066 | - |
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+ | 2.0 | 800 | 0.0194 | - |
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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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