---
library_name: setfit
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
metrics:
- accuracy
widget:
- text: 'The Vitorian team knew to make up for the significant absences of Herrmann
    , Oleson , Huertas and Micov with a big dose of involvement and teamwork , even
    though it had to hold out until the end to take the victory . '
- text: '`` But why pay her bills ? '
- text: 'In the body , pemetrexed is converted into an active form that blocks the
    activity of the enzymes that are involved in producing nucleotides ( the building
    blocks of DNA and RNA , the genetic material of cells ) . '
- text: '`` The daily crush of media tweets , cameras and reporters outside the courthouse
    , '''' the lawyers wrote , `` was unlike anything ever seen here in New Haven
    and maybe statewide . '''' '
- text: 'However , in both studies , patients whose cancer was not affecting squamous
    cells had longer survival times if they received Alimta than if they received
    the comparator . '
pipeline_tag: text-classification
inference: true
base_model: sentence-transformers/paraphrase-mpnet-base-v2
---

# 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 [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) 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 [SetFitHead](huggingface.co/docs/setfit/reference/main#setfit.SetFitHead) instance
- **Maximum Sequence Length:** 512 tokens
- **Number of Classes:** 7 classes
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### 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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
|:------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 6     | <ul><li>'If you were especially helpful in a corrupt scheme you received not just cash in a bag , but equity . '</li><li>'Two American companies reached deals for fields auctioned in June . '</li><li>'Let me prove it , Phil . '</li></ul>                                                                                                                                                                                                                                                                                                                                                          |
| 2     | <ul><li>'This building shook like hell and it kept getting stronger . '</li><li>'Now you could ask me , why should the user mind about MathML ? '</li><li>'The report and a casebook of initiatives will be published in 1996 and provide the backdrop for a conference to be staged in Autumn , 1996 . '</li></ul>                                                                                                                                                                                                                                                                                    |
| 3     | <ul><li>'The tumor , he suggested , developed when the second , normal copy also was damaged . '</li><li>'Proper English bells are started off in `` rounds , `` from the highest-pitched bell to the lowest -- a simple descending scale using , in larger churches , as many as 12 bells . '</li><li>'Treatment should be delayed or discontinued , or the dose reduced , in patients whose blood counts are abnormal or who have certain other side effects . '</li></ul>                                                                                                                           |
| 5     | <ul><li>'Schools that are structured in this way produce students with higher morale and superior academic performance . '</li><li>'I got home , let the dogs into the house and noticed some sounds above my head , as if someone were walking on the roof , or upstairs . '</li><li>'Give me your address . '</li></ul>                                                                                                                                                                                                                                                                              |
| 0     | <ul><li>'-- Most important of all , schools should have principals with a large measure of authority over the faculty , the curriculum , and all matters of student discipline . '</li><li>'For months the Johns Hopkins researchers , using gene probes , experimentally crawled down the length of chromosome 17 , looking for the smallest common bit of genetic material lost in all tumor cells . '</li><li>'It explains how the Committee for Medicinal Products for Human Use ( CHMP ) assessed the studies performed , to reach their recommendations on how to use the medicine . '</li></ul> |
| 4     | <ul><li>'In 2005 , the fear of invasion of the national territory by hordes of Polish plumbers was felt both on the Left and on the Right . '</li><li>'Cerenia contains the active substance maropitant and is available as tablet or as solution for injection . '</li><li>'The second quarter was more of the same , but the Alavan team opted for the inside game of Barac and the work of Eliyahu , who was greeted with whistles and applause at his return home , to continue increasing their lead by half-time ( 34-43 ) . '</li></ul>                                                         |
| 1     | <ul><li>'`` The sound of bells is a net to draw people into the church , `` he says . '</li><li>'`` Progressive education `` ( as it was once called ) is far more interesting and agreeable to teachers than is disciplined instruction . '</li><li>"The defense lawyers also claim , for example , that Mr. Hayes may have been prejudiced when Judge Blue declined to allow them to test potential jurors ' reactions by showing them grisly crime-scene photographs during jury selection . "</li></ul>                                                                                            |

## 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("HelgeKn/SemEval-multi-class-v1-10")
# Run inference
preds = model("`` But why pay her bills ? ")
```

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## Training Details

### Training Set Metrics
| Training set | Min | Median  | Max |
|:-------------|:----|:--------|:----|
| Word count   | 5   | 25.8286 | 75  |

| Label | Training Sample Count |
|:------|:----------------------|
| 0     | 10                    |
| 1     | 10                    |
| 2     | 10                    |
| 3     | 10                    |
| 4     | 10                    |
| 5     | 10                    |
| 6     | 10                    |

### Training Hyperparameters
- batch_size: (16, 16)
- num_epochs: (4, 4)
- max_steps: -1
- sampling_strategy: oversampling
- num_iterations: 20
- body_learning_rate: (2e-05, 2e-05)
- head_learning_rate: 2e-05
- 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 |
|:------:|:----:|:-------------:|:---------------:|
| 0.0057 | 1    | 0.2314        | -               |
| 0.2857 | 50   | 0.218         | -               |
| 0.5714 | 100  | 0.1161        | -               |
| 0.8571 | 150  | 0.0559        | -               |
| 1.1429 | 200  | 0.0087        | -               |
| 1.4286 | 250  | 0.0029        | -               |
| 1.7143 | 300  | 0.001         | -               |
| 2.0    | 350  | 0.0006        | -               |
| 2.2857 | 400  | 0.0011        | -               |
| 2.5714 | 450  | 0.0009        | -               |
| 2.8571 | 500  | 0.0005        | -               |
| 3.1429 | 550  | 0.0006        | -               |
| 3.4286 | 600  | 0.0004        | -               |
| 3.7143 | 650  | 0.0003        | -               |
| 4.0    | 700  | 0.0005        | -               |

### Framework Versions
- Python: 3.9.13
- SetFit: 1.0.1
- Sentence Transformers: 2.2.2
- Transformers: 4.36.0
- PyTorch: 2.1.1+cpu
- Datasets: 2.15.0
- 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}
}
```

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