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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: Artificial intelligence is changing the way we live and work. |
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- text: The university is offering scholarships for students in financial need. |
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- text: The new Marvel movie is breaking box office records. |
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- text: The annual Met Gala is a major event in the fashion world. |
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- text: Visiting the Grand Canyon is a breathtaking experience. |
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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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--- |
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# SetFit with sentence-transformers/paraphrase-mpnet-base-v2 |
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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 [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. |
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The model has been trained using an efficient few-shot learning technique that involves: |
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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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## Model Details |
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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 [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance |
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- **Maximum Sequence Length:** 512 tokens |
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- **Number of Classes:** 12 classes |
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### Model Sources |
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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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### Model Labels |
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| Label | Examples | |
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|:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |
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| 0 | <ul><li>'The mayor announced a new initiative to improve public transportation.'</li><li>'The senator is facing criticism for her stance on the recent bill.'</li><li>'The upcoming election has sparked intense debates among the candidates.'</li></ul> | |
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| 3 | <ul><li>'Regular exercise and a balanced diet are key to maintaining good health.'</li><li>'The World Health Organization has issued new guidelines on COVID-19.'</li><li>'A new study reveals the benefits of meditation for mental health.'</li></ul> | |
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| 6 | <ul><li>'The stock market saw a significant drop following the announcement.'</li><li>'Investing in real estate can be a profitable venture if done correctly.'</li><li>"The company's profits have doubled since the launch of their new product."</li></ul> | |
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| 9 | <ul><li>'Visiting the Grand Canyon is a breathtaking experience.'</li><li>'The tourism industry has been severely impacted by the pandemic.'</li><li>'Backpacking through Europe is a popular choice for young travelers.'</li></ul> | |
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| 12 | <ul><li>'The new restaurant in town offers a fusion of Italian and Japanese cuisine.'</li><li>'Drinking eight glasses of water a day is essential for staying hydrated.'</li><li>'Cooking classes are a fun way to learn new recipes and techniques.'</li></ul> | |
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| 15 | <ul><li>'The school district is implementing a new curriculum for the upcoming year.'</li><li>'Online learning has become increasingly popular during the pandemic.'</li><li>'The university is offering scholarships for students in financial need.'</li></ul> | |
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| 18 | <ul><li>'Climate change is causing a significant rise in sea levels.'</li><li>'Recycling and composting are effective ways to reduce waste.'</li><li>'The Amazon rainforest is home to millions of unique species.'</li></ul> | |
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| 21 | <ul><li>'The new fashion trend is all about sustainability and eco-friendly materials.'</li><li>'The annual Met Gala is a major event in the fashion world.'</li><li>'Vintage clothing has made a comeback in recent years.'</li></ul> | |
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| 24 | <ul><li>"NASA's Mars Rover has made significant discoveries about the red planet."</li><li>'The Nobel Prize in Physics was awarded for breakthroughs in black hole research.'</li><li>'Genetic engineering is opening up new possibilities in medical treatment.'</li></ul> | |
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| 27 | <ul><li>'The NBA Finals are set to begin next week with the top two teams in the league.'</li><li>'Serena Williams continues to dominate the tennis world with her powerful serve.'</li><li>'The World Cup is the most prestigious tournament in international soccer.'</li></ul> | |
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| 30 | <ul><li>'Artificial intelligence is changing the way we live and work.'</li><li>'The latest iPhone has a number of exciting new features.'</li><li>'Cybersecurity is becoming increasingly important as more and more data moves online.'</li></ul> | |
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| 33 | <ul><li>'The new Marvel movie is breaking box office records.'</li><li>'The Grammy Awards are a celebration of the best music of the year.'</li><li>'The latest season of Game of Thrones had fans on the edge of their seats.'</li></ul> | |
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## Uses |
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### Direct Use for Inference |
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First install the SetFit library: |
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```bash |
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pip install setfit |
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``` |
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Then you can load this model and run inference. |
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```python |
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from setfit import SetFitModel |
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# Download from the 🤗 Hub |
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model = SetFitModel.from_pretrained("EmeraldMP/ANLP_kaggle") |
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# Run inference |
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preds = model("The new Marvel movie is breaking box office records.") |
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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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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
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## Training Details |
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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 | 8 | 11.0833 | 17 | |
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| Label | Training Sample Count | |
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|:------|:----------------------| |
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| 0 | 3 | |
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| 3 | 3 | |
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| 6 | 3 | |
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| 9 | 3 | |
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| 12 | 3 | |
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| 15 | 3 | |
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| 18 | 3 | |
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| 21 | 3 | |
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| 24 | 3 | |
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| 27 | 3 | |
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| 30 | 3 | |
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| 33 | 3 | |
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### Training Hyperparameters |
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- batch_size: (16, 16) |
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- num_epochs: (1, 1) |
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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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### Training Results |
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| Epoch | Step | Training Loss | Validation Loss | |
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|:------:|:----:|:-------------:|:---------------:| |
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| 0.0111 | 1 | 0.1765 | - | |
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| 0.5556 | 50 | 0.0137 | - | |
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### Framework Versions |
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- Python: 3.10.12 |
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- SetFit: 1.0.3 |
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- Sentence Transformers: 2.7.0 |
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- Transformers: 4.38.2 |
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- PyTorch: 2.2.1+cu121 |
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- Datasets: 2.18.0 |
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- Tokenizers: 0.15.2 |
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## Citation |
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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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