
# 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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
|:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 3     | <ul><li>'There were relatively few cases reported of attempts to involve users in service planning but their involvement in service provision was found to be more common . '</li><li>"At St. Mary 's Church in Ilminster , Somerset , the bells have fallen silent following a dust-up over church attendance . "</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>                                                                                                                                                                                                                                                                                                                |
| 6     | <ul><li>'If you were especially helpful in a corrupt scheme you received not just cash in a bag , but equity . '</li><li>"Moreover , conservatives argue that it 's Justice Elena Kagan who has an ethical issue , not Scalia and Thomas . "</li><li>'No one speaks , and the snaking of the ropes seems to make as much sound as the bells themselves , muffled by the ceiling . '</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                   |
| 2     | <ul><li>'In and around all levels of government in the U.S. are groups of people who can best be described as belonging to a political insider commercial party . '</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><li>'This building shook like hell and it kept getting stronger . '</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                   |
| 0     | <ul><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><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></ul>                                                                                                                                                                                                          |
| 5     | <ul><li>': = : It is used to define a variable value . '</li><li>'I could also see the clouds across the bay from the horrible fire in the Marina District of San Francisco . '</li><li>'The man with the clipboard represented a halfhearted attempt to introduce a bit of les sportif into our itinerary . '</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
| 4     | <ul><li>"First , why ticket splitting has increased and taken the peculiar pattern that it has over the past half century : Prior to the election of Franklin Roosevelt as president and the advent of the New Deal , government occupied a much smaller role in society and the prisoner 's dilemma problem confronting voters in races for Congress was considerably less severe . "</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><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></ul> |
| 1     | <ul><li>'`` Progressive education `` ( as it was once called ) is far more interesting and agreeable to teachers than is disciplined instruction . '</li><li>"Ringing does become a bit of an obsession , `` admits Stephanie Pattenden , master of the band at St. Mary Abbot and one of England 's best female ringers . "</li><li>"He says the neighbors complain , but I do n't believe it . "</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                    |

## Evaluation

### Metrics
| Label   | Accuracy |
|:--------|:---------|
| **all** | 0.1616   |

## 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-label-v2")
# 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   | 6   | 25.8929 | 75  |

| Label | Training Sample Count |
|:------|:----------------------|
| 0     | 8                     |
| 1     | 8                     |
| 2     | 8                     |
| 3     | 8                     |
| 4     | 8                     |
| 5     | 8                     |
| 6     | 8                     |

### Training Hyperparameters
- batch_size: (16, 16)
- num_epochs: (1, 1)
- 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 |
|:------:|:----:|:-------------:|:---------------:|
| 0.0071 | 1    | 0.2758        | -               |
| 0.3571 | 50   | 0.1622        | -               |
| 0.7143 | 100  | 0.0874        | -               |

### 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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{"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", "model-index": [{"name": "SetFit with sentence-transformers/paraphrase-mpnet-base-v2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "Unknown", "type": "unknown", "split": "test"}, "metrics": [{"type": "accuracy", "value": 0.16158940397350993, "name": "Accuracy"}]}]}]}
setfit safetensors mpnet sentence-transformers text-classification generated_from_setfit_trainer arxiv:2209.11055 base_model:sentence-transformers/paraphrase-mpnet-base-v2 model-index region:us