---
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: handling washing radiation precaution long leaving scientist tongs source
effective nature air range row laboratory low experiment keeping sealed temperature
opening protect
- text: nucleus proton element charge isotope
- text: size mean al time sound tuning frequency every marked last second length note
directly produced fork number travel
- text: distance circle surface stick frequency water dipped correct vertical longitudinal
three produced statement two amplitude wave
- text: rate electromagnetic radiation source correct form stream radioactive penetrating
detector statement highly
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: 0.9387755102040817
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 [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) 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 [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
- **Maximum Sequence Length:** 512 tokens
- **Number of Classes:** 6 classes
### 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 |
|:------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| wave |
- 'sound infrared wave ultraviolet transverse list diagram light'
- 'size mean al time sound tuning frequency every marked last second length note directly produced fork number travel'
- 'nearby series sound higher frequency air rarefaction correctly pressure amplitude compression row certain lower wave'
|
| forces | - 'extension diagram spring free load three applied handle'
- 'different extension spring elastic student proportional length directly object weight diagram cord mass much hung'
- 'distance plank long ground load force beam mass value'
|
| electricity | - 'two diagram circuit parallel connected'
- 'lamp resistance student various thermistor current circuit parallel happen'
- 'resistance student two shown reading ammeter resistor identical circuit voltmeter determine'
|
| magnetism | - 'bar suitable two across made magnet metal electromagnet diagram permanent core'
- 'magnetic student hard magnet rod iron material magnetism correct use statement steel permanent soft make'
- 'magnetic bar student two hard magnet rod iron material close nickel use steel permanent soft make'
|
| nuclear | - 'nucleus proton element charge isotope'
- 'different five'
- 'rate electromagnetic radiation source correct form stream radioactive penetrating detector statement highly'
|
| thermal | - 'cooling air top unit stay density transfer correct near thermal move diagram statement refrigerator energy movement'
- 'dense position air cold warmer heater flask two room fit less hot possible fitted diagram warm throughout um liquid better'
- 'power balance copper student thermometer heat heater substance watch calculate need specific initially solid mass apparatus block capacity electrical key'
|
## Evaluation
### Metrics
| Label | Accuracy |
|:--------|:---------|
| **all** | 0.9388 |
## 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("Aurore32/physics-classifier-model")
# Run inference
preds = model("nucleus proton element charge isotope")
```
## Training Details
### Training Set Metrics
| Training set | Min | Median | Max |
|:-------------|:----|:-------|:----|
| Word count | 2 | 13.375 | 35 |
| Label | Training Sample Count |
|:------------|:----------------------|
| wave | 8 |
| wave | 8 |
| magnetism | 8 |
| wave | 8 |
| magnetism | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| nuclear | 8 |
| thermal | 8 |
| nuclear | 8 |
| electricity | 8 |
| nuclear | 8 |
| forces | 8 |
| wave | 8 |
| nuclear | 8 |
| forces | 8 |
| thermal | 8 |
| wave | 8 |
| nuclear | 8 |
| thermal | 8 |
| nuclear | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| electricity | 8 |
| electricity | 8 |
| thermal | 8 |
| forces | 8 |
| electricity | 8 |
| nuclear | 8 |
| thermal | 8 |
| magnetism | 8 |
| thermal | 8 |
| thermal | 8 |
| forces | 8 |
| wave | 8 |
| nuclear | 8 |
| nuclear | 8 |
| wave | 8 |
| thermal | 8 |
| magnetism | 8 |
| forces | 8 |
| magnetism | 8 |
| electricity | 8 |
| nuclear | 8 |
| magnetism | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| wave | 8 |
| nuclear | 8 |
| nuclear | 8 |
| magnetism | 8 |
| electricity | 8 |
| wave | 8 |
| nuclear | 8 |
| electricity | 8 |
| magnetism | 8 |
| magnetism | 8 |
| forces | 8 |
| electricity | 8 |
| wave | 8 |
| nuclear | 8 |
| nuclear | 8 |
| nuclear | 8 |
| electricity | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| thermal | 8 |
| nuclear | 8 |
| wave | 8 |
| wave | 8 |
| forces | 8 |
| wave | 8 |
| electricity | 8 |
| nuclear | 8 |
| wave | 8 |
| magnetism | 8 |
| wave | 8 |
| thermal | 8 |
| electricity | 8 |
| thermal | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| wave | 8 |
| forces | 8 |
| nuclear | 8 |
| thermal | 8 |
| thermal | 8 |
| magnetism | 8 |
| electricity | 8 |
| nuclear | 8 |
| magnetism | 8 |
| magnetism | 8 |
| wave | 8 |
| electricity | 8 |
| forces | 8 |
| magnetism | 8 |
| wave | 8 |
| magnetism | 8 |
| electricity | 8 |
| thermal | 8 |
| magnetism | 8 |
| forces | 8 |
| magnetism | 8 |
| magnetism | 8 |
| magnetism | 8 |
| thermal | 8 |
| electricity | 8 |
| thermal | 8 |
| nuclear | 8 |
| wave | 8 |
| thermal | 8 |
| nuclear | 8 |
| magnetism | 8 |
| wave | 8 |
| thermal | 8 |
| electricity | 8 |
| thermal | 8 |
| thermal | 8 |
| magnetism | 8 |
| thermal | 8 |
| magnetism | 8 |
| electricity | 8 |
| forces | 8 |
| nuclear | 8 |
| nuclear | 8 |
| wave | 8 |
| magnetism | 8 |
| wave | 8 |
| thermal | 8 |
| thermal | 8 |
| wave | 8 |
| nuclear | 8 |
| electricity | 8 |
| forces | 8 |
| wave | 8 |
| forces | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| nuclear | 8 |
| electricity | 8 |
| wave | 8 |
| thermal | 8 |
| electricity | 8 |
| thermal | 8 |
| electricity | 8 |
| electricity | 8 |
| magnetism | 8 |
| wave | 8 |
| thermal | 8 |
| nuclear | 8 |
| nuclear | 8 |
| magnetism | 8 |
| thermal | 8 |
| electricity | 8 |
| thermal | 8 |
| electricity | 8 |
| nuclear | 8 |
| electricity | 8 |
| wave | 8 |
| forces | 8 |
| nuclear | 8 |
| wave | 8 |
| nuclear | 8 |
| forces | 8 |
| thermal | 8 |
| forces | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| forces | 8 |
| thermal | 8 |
| thermal | 8 |
| forces | 8 |
| forces | 8 |
| wave | 8 |
| thermal | 8 |
| nuclear | 8 |
| magnetism | 8 |
| electricity | 8 |
| wave | 8 |
| forces | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| magnetism | 8 |
| wave | 8 |
| electricity | 8 |
| wave | 8 |
| wave | 8 |
| electricity | 8 |
| magnetism | 8 |
| wave | 8 |
| electricity | 8 |
| forces | 8 |
| electricity | 8 |
| thermal | 8 |
| magnetism | 8 |
| nuclear | 8 |
| thermal | 8 |
| wave | 8 |
| wave | 8 |
| thermal | 8 |
| electricity | 8 |
| electricity | 8 |
| wave | 8 |
| forces | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| thermal | 8 |
| electricity | 8 |
| magnetism | 8 |
| electricity | 8 |
| magnetism | 8 |
| nuclear | 8 |
| electricity | 8 |
| electricity | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| nuclear | 8 |
| nuclear | 8 |
| wave | 8 |
| thermal | 8 |
| thermal | 8 |
| nuclear | 8 |
| electricity | 8 |
| magnetism | 8 |
| nuclear | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| nuclear | 8 |
| thermal | 8 |
| magnetism | 8 |
| magnetism | 8 |
| electricity | 8 |
| thermal | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| nuclear | 8 |
| electricity | 8 |
| electricity | 8 |
| electricity | 8 |
| magnetism | 8 |
| electricity | 8 |
| thermal | 8 |
| electricity | 8 |
| thermal | 8 |
| electricity | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| nuclear | 8 |
| wave | 8 |
| forces | 8 |
| wave | 8 |
| electricity | 8 |
| forces | 8 |
| forces | 8 |
| wave | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| magnetism | 8 |
| electricity | 8 |
| forces | 8 |
| forces | 8 |
| thermal | 8 |
| magnetism | 8 |
| forces | 8 |
| magnetism | 8 |
| magnetism | 8 |
| thermal | 8 |
| electricity | 8 |
| forces | 8 |
| electricity | 8 |
| magnetism | 8 |
| thermal | 8 |
| forces | 8 |
| magnetism | 8 |
| nuclear | 8 |
| nuclear | 8 |
| nuclear | 8 |
| electricity | 8 |
| nuclear | 8 |
| wave | 8 |
| nuclear | 8 |
| magnetism | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| nuclear | 8 |
| nuclear | 8 |
| nuclear | 8 |
| magnetism | 8 |
| electricity | 8 |
| magnetism | 8 |
| forces | 8 |
| wave | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| magnetism | 8 |
| wave | 8 |
| thermal | 8 |
| forces | 8 |
| magnetism | 8 |
| nuclear | 8 |
| thermal | 8 |
| magnetism | 8 |
| magnetism | 8 |
| magnetism | 8 |
| magnetism | 8 |
| thermal | 8 |
| thermal | 8 |
| electricity | 8 |
| wave | 8 |
| magnetism | 8 |
| thermal | 8 |
| magnetism | 8 |
| wave | 8 |
| forces | 8 |
| thermal | 8 |
| thermal | 8 |
| electricity | 8 |
| thermal | 8 |
| forces | 8 |
| nuclear | 8 |
| wave | 8 |
| electricity | 8 |
| wave | 8 |
| wave | 8 |
| magnetism | 8 |
| electricity | 8 |
| wave | 8 |
| electricity | 8 |
| thermal | 8 |
| nuclear | 8 |
| wave | 8 |
| magnetism | 8 |
| thermal | 8 |
| wave | 8 |
| thermal | 8 |
| nuclear | 8 |
| thermal | 8 |
| wave | 8 |
| wave | 8 |
| thermal | 8 |
| electricity | 8 |
| electricity | 8 |
| thermal | 8 |
| electricity | 8 |
| magnetism | 8 |
| magnetism | 8 |
| thermal | 8 |
| electricity | 8 |
| magnetism | 8 |
| thermal | 8 |
| thermal | 8 |
| magnetism | 8 |
| magnetism | 8 |
| wave | 8 |
| electricity | 8 |
| thermal | 8 |
| magnetism | 8 |
| nuclear | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| wave | 8 |
| electricity | 8 |
| forces | 8 |
| forces | 8 |
| electricity | 8 |
| magnetism | 8 |
| thermal | 8 |
| magnetism | 8 |
| thermal | 8 |
| nuclear | 8 |
| thermal | 8 |
| magnetism | 8 |
| electricity | 8 |
| nuclear | 8 |
| forces | 8 |
| wave | 8 |
| thermal | 8 |
| wave | 8 |
| forces | 8 |
| thermal | 8 |
| magnetism | 8 |
| electricity | 8 |
| magnetism | 8 |
| wave | 8 |
| nuclear | 8 |
| wave | 8 |
| forces | 8 |
| thermal | 8 |
| magnetism | 8 |
| forces | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| thermal | 8 |
| thermal | 8 |
| electricity | 8 |
| nuclear | 8 |
| wave | 8 |
| nuclear | 8 |
| magnetism | 8 |
| magnetism | 8 |
| thermal | 8 |
| magnetism | 8 |
| electricity | 8 |
| magnetism | 8 |
| magnetism | 8 |
| thermal | 8 |
| wave | 8 |
| nuclear | 8 |
| nuclear | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| nuclear | 8 |
| nuclear | 8 |
| thermal | 8 |
| forces | 8 |
| wave | 8 |
| forces | 8 |
| wave | 8 |
| nuclear | 8 |
| forces | 8 |
| wave | 8 |
| magnetism | 8 |
| nuclear | 8 |
| wave | 8 |
| magnetism | 8 |
| electricity | 8 |
| electricity | 8 |
| wave | 8 |
| nuclear | 8 |
| electricity | 8 |
| electricity | 8 |
| wave | 8 |
| wave | 8 |
| forces | 8 |
| nuclear | 8 |
| nuclear | 8 |
| magnetism | 8 |
| thermal | 8 |
| nuclear | 8 |
| nuclear | 8 |
| thermal | 8 |
| wave | 8 |
| nuclear | 8 |
| forces | 8 |
| nuclear | 8 |
| thermal | 8 |
| magnetism | 8 |
| wave | 8 |
| nuclear | 8 |
| thermal | 8 |
| thermal | 8 |
| magnetism | 8 |
| electricity | 8 |
| wave | 8 |
| wave | 8 |
| electricity | 8 |
| wave | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| nuclear | 8 |
| forces | 8 |
| wave | 8 |
| electricity | 8 |
| wave | 8 |
| forces | 8 |
| thermal | 8 |
| thermal | 8 |
| magnetism | 8 |
| wave | 8 |
| electricity | 8 |
| nuclear | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| thermal | 8 |
| electricity | 8 |
| nuclear | 8 |
| thermal | 8 |
| nuclear | 8 |
| wave | 8 |
| wave | 8 |
| forces | 8 |
| electricity | 8 |
| thermal | 8 |
| wave | 8 |
| nuclear | 8 |
| nuclear | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| nuclear | 8 |
| wave | 8 |
| nuclear | 8 |
| wave | 8 |
| wave | 8 |
| magnetism | 8 |
| nuclear | 8 |
| forces | 8 |
| magnetism | 8 |
| magnetism | 8 |
| wave | 8 |
| nuclear | 8 |
| forces | 8 |
| magnetism | 8 |
| thermal | 8 |
| wave | 8 |
| magnetism | 8 |
| thermal | 8 |
| nuclear | 8 |
| wave | 8 |
| electricity | 8 |
| wave | 8 |
| magnetism | 8 |
| electricity | 8 |
| magnetism | 8 |
| thermal | 8 |
| forces | 8 |
| forces | 8 |
| thermal | 8 |
| wave | 8 |
| electricity | 8 |
| wave | 8 |
| electricity | 8 |
| wave | 8 |
| thermal | 8 |
| thermal | 8 |
| nuclear | 8 |
| electricity | 8 |
| forces | 8 |
| nuclear | 8 |
| magnetism | 8 |
| magnetism | 8 |
| wave | 8 |
| nuclear | 8 |
| forces | 8 |
| wave | 8 |
| forces | 8 |
| magnetism | 8 |
| thermal | 8 |
| nuclear | 8 |
| thermal | 8 |
| electricity | 8 |
### Training Hyperparameters
- batch_size: (16, 2)
- num_epochs: (1, 16)
- max_steps: -1
- sampling_strategy: oversampling
- body_learning_rate: (2e-05, 1e-05)
- head_learning_rate: 0.01
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- l2_weight: 0.01
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
### Training Results
| Epoch | Step | Training Loss | Validation Loss |
|:------:|:----:|:-------------:|:---------------:|
| 0.0083 | 1 | 0.1733 | - |
| 0.4167 | 50 | 0.075 | - |
| 0.8333 | 100 | 0.0056 | - |
### Framework Versions
- Python: 3.12.4
- SetFit: 1.1.1
- Sentence Transformers: 3.4.0
- Transformers: 4.44.2
- PyTorch: 2.5.1+cpu
- Datasets: 3.2.0
- Tokenizers: 0.19.1
## 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}
}
```