setfit safetensors mpnet sentence-transformers text-classification generated_from_setfit_trainer arxiv:2209.11055 base_model:sentence-transformers/paraphrase-mpnet-base-v2 base_model:finetune:sentence-transformers/paraphrase-mpnet-base-v2 model-index region:us
---
base_model: sentence-transformers/paraphrase-mpnet-base-v2
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: Buses are more simple - you just buy a ticket .
- text: As citizens of village , we totally care about environment of our village
    .
- text: So , finally I suggest that it would be a great idea to combine the different
    types of activities , both popular and the newest .
- text: Had 12 years old .
- text: On the other hand , I have the theoretical knowledge to use new the technologies
    this great project requires .
inference: true
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: 0.15543478260869564
      name: Accuracy
---

# 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:** 8 classes
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->

### 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>"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>'While youngsters use their time trying to get concerned the oldest people from de village about the importance of the care of our surroundings , middle - aged people planted many trees around the village and cleaned the floor of our public places making a more attractive place to live than we used to have .'</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> |
| 5     | <ul><li>'Michael get away from there .'</li><li>'I guess that in our future there are no helicopters , and not even cars .'</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>                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
| 4     | <ul><li>'Something that they don know was that the whole thing was a movie !'</li><li>'Yours Sincerely .'</li><li>"stop shouting . do n't shout ."</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| 2     | <ul><li>'X " admitted to a state psychiatric hospital after being found not competent to stand trial on charges of stalking harassment , trespassing and telephone harassment " ( pp .'</li><li>'It is a job with a lot of interesting aspects ,'</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></ul>                                                                                                                                                                                                                                                                                                       |
| 6     | <ul><li>'In addition , she has no blithe memory in her childhood .'</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><li>'I know you are searching for a flat to live for the whole next year .'</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| 0     | <ul><li>'In China , English is took to be a foreign language which many students choose to learn .'</li><li>'No one can deny that the pollution issue is one of the utmost important thing which should be prevented .'</li><li>'The third section is to print the prepared bank notes .'</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
| 1     | <ul><li>'They use at least one hour to learn English knowledge a day .'</li><li>'If you want to see that movie , you need to watch the first 3 movies before to understand it .'</li><li>'Next to go would be , students get used to relax by having no study and homework in the long vacation .'</li></ul>                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| 7     | <ul><li>'To start with , there are a wide range of troublesome it maybe leadding to this phenomeon .'</li><li>'Secondly , the families could give you some advice about how to deal with the things which will cause trouble .'</li><li>'I been twelve years practice volleyball and because of it I knew lot of people who help me to grow up in the sport and life .'</li></ul>                                                                                                                                                                                                                                                                                                                                                                                     |

## Evaluation

### Metrics
| Label   | Accuracy |
|:--------|:---------|
| **all** | 0.1554   |

## 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/BEA2019-multi-class-10")
# Run inference
preds = model("Had 12 years old .")
```

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## Training Details

### Training Set Metrics
| Training set | Min | Median  | Max |
|:-------------|:----|:--------|:----|
| Word count   | 3   | 21.3375 | 56  |

| Label | Training Sample Count |
|:------|:----------------------|
| 0     | 10                    |
| 1     | 10                    |
| 2     | 10                    |
| 3     | 10                    |
| 4     | 10                    |
| 5     | 10                    |
| 6     | 10                    |
| 7     | 10                    |

### Training Hyperparameters
- batch_size: (16, 16)
- num_epochs: (2, 2)
- 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 |
|:-----:|:----:|:-------------:|:---------------:|
| 0.005 | 1    | 0.2242        | -               |
| 0.25  | 50   | 0.1786        | -               |
| 0.5   | 100  | 0.1831        | -               |
| 0.75  | 150  | 0.0221        | -               |
| 1.0   | 200  | 0.0127        | -               |
| 1.25  | 250  | 0.0064        | -               |
| 1.5   | 300  | 0.0045        | -               |
| 1.75  | 350  | 0.0028        | -               |
| 2.0   | 400  | 0.002         | -               |

### 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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