---
base_model: sentence-transformers/paraphrase-mpnet-base-v2
datasets:
- fancyzhx/ag_news
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: Google gets a bounce, ends its first day up 18 percent Shares of Google leaped
    \$15.34, or 18 percent, to \$100.34 on the Nasdaq exchange yesterday in an opening
    day of trading that harkened back to the wild run-ups of the dot-com era.
- text: Jobs Data Hold Promise of Stronger Growth (AP) AP - Employers stepped up hiring
    in August, expanding payrolls by 144,000 and lowering the unemployment rate marginally
    to 5.4 percent. While the figures didn't amount to a national job fair, analysts
    said, they did hold out the promise of stronger growth following the summer lull.
- text: Canadians in Southeast Asia at risk from terrorist groups, report cautions
    (Canadian Press) Canadian Press - OTTAWA (CP) - Islamic extremists with links
    to Osama bin Laden's al-Qaida network pose a threat to Canadians living in Southeast
    Asia, warns a newly obtained intelligence report.
- text: 'Cricket telecast: Opportunity for lost bidders EVEN as Zee Telefilms chalks
    out its strategy for the cricket rights, legal experts are of the opinion that
    the Bombay High Court #39;s suggestion for a fresh round of bidding could open
    options for the other broadcasters who had lost out in the first round.'
- text: UN Security Council to Witness Sudan Peace Pledge  NAIROBI (Reuters) - The
    Sudanese government and its  southern rebel opponents have agreed to sign a pledge
    in the  Kenyan capital on Friday to formally end a brutal 21-year-old  civil war,
    with U.N. Security Council ambassadors as witnesses.
inference: true
model-index:
- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: fancyzhx/ag_news
      type: fancyzhx/ag_news
      split: test
    metrics:
    - type: accuracy
      value: 0.7647368421052632
      name: Accuracy
---

# SetFit with sentence-transformers/paraphrase-mpnet-base-v2

This is a [SetFit](https://github.com/huggingface/setfit) model trained on the [fancyzhx/ag_news](https://huggingface.co/datasets/fancyzhx/ag_news) dataset 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:** 4 classes
- **Training Dataset:** [fancyzhx/ag_news](https://huggingface.co/datasets/fancyzhx/ag_news)
<!-- - **Language:** Unknown -->
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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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
|:---------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Sci/Tech | <ul><li>'MIT Selects Its First Female President (Reuters) Reuters - The Massachusetts Institute of\\Technology on Thursday named Susan Hockfield as its first\\female president, a breakthrough for the world-renowned school\\that has churned out more than 50 Nobel prizewinners but which\\ranks below the national average for its percentage of female\\students.'</li><li>"New PC Is Created Just for Teenagers (AP) AP - This isn't your typical, humdrum, slate-colored computer. Not only is the PC known as the hip-e almost all white, but its screen and keyboard are framed in fuzzy pink fur. Or a leopard skin design. Or a graffiti-themed pattern."</li><li>'Cdn X Prize team postpones launch KINDERSLEY, Sask. (CP) -- A Canadian team of engineers competing in an international race to put civilians into space has postponed its first stab at the \\$10-million prize.'</li></ul>      |
| Business | <ul><li>'Cold sends oil price above \\$44 Oil futures prices have jumped 5 percent higher, climbing above \\$44 a barrel in the United States Wednesday after US government data showed a slight decline in crude and heating oil supplies as colder weather in the Northeast drove up '</li><li>"2 Cable Giants Set To Bid for Adelphia Comcast Corp. and Time Warner Inc. are planning a joint bid for Adelphia Communications Corp. as part of a deal that could lead to a broad realignment of interests in the cable industry and increase Comcast's already dominant presence in the mid-Atlantic region."</li><li>'Piper Rudnick to Merge With Big British Firm Piper Rudnick Gray Cary LLP, a law firm with major operations in Washington, agreed over the weekend to merge with British firm DLA LLP, creating one of the largest combinations ever of law firms from different countries.'</li></ul> |
| World    | <ul><li>'50 Hurt During Opposition Strike in Bangladesh Capital In Bangladesh, at least 50 people have been injured in clashes with authorities during a general strike called by the main opposition party.'</li><li>"No Time Frame for Yuan Move -China  WASHINGTON (Reuters) - There is no time frame for a shift  away from Beijing's tight currency peg and the United States is  mistaken if it thinks it will reap big benefits from a move, a  top Chinese central bank official said on Sunday."</li><li>'American Forces Bomb Site in Fallujah (AP) AP - American forces bombed a site in the insurgent stronghold of Fallujah early Tuesday where several militants loyal to terror mastermind Abu Musab al-Zarqawi were believed to be holed up, the U.S. military said.'</li></ul>                                                                                                                 |
| Sports   | <ul><li>'Blue Jays activate Halladay from DL Bronx, NY (Sports Network) - The Toronto Blue Jays activated pitcher Roy Halladay from the 15-day disabled list and he is expected to start Tuesday #39;s game against the New York Yankees.'</li><li>'Trinidad climbs off canvas to keep title options open Felix Trinidad returned to the ring after more than two years to score a thrilling eighth-round stoppage of Ricardo Mayorga at New York #39;s Madison Square Garden in a non- title bout being described as one of the fights of the year.'</li><li>'Broncos #39; rout frustrates Saints owner NEW ORLEANS -- Another blowout loss left New Orleans owner Tom Benson furious and wondering whether his team belonged in the NFL. Reuben Droughns rushed for 166 yards and a touchdown, Jake Plummer threw for '</li></ul>                                                                             |

## Evaluation

### Metrics
| Label   | Accuracy |
|:--------|:---------|
| **all** | 0.7647   |

## 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("setfit_model_id")
# Run inference
preds = model("Google gets a bounce, ends its first day up 18 percent Shares of Google leaped \$15.34, or 18 percent, to \$100.34 on the Nasdaq exchange yesterday in an opening day of trading that harkened back to the wild run-ups of the dot-com era.")
```

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## Training Details

### Training Set Metrics
| Training set | Min | Median  | Max |
|:-------------|:----|:--------|:----|
| Word count   | 14  | 39.5694 | 62  |

| Label    | Training Sample Count |
|:---------|:----------------------|
| World    | 28                    |
| Sports   | 16                    |
| Business | 18                    |
| Sci/Tech | 10                    |

### Training Hyperparameters
- batch_size: (16, 16)
- num_epochs: (5, 5)
- 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
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: True

### Training Results
| Epoch   | Step    | Training Loss | Validation Loss |
|:-------:|:-------:|:-------------:|:---------------:|
| 0.0043  | 1       | 0.4093        | -               |
| 0.2146  | 50      | 0.2095        | -               |
| 0.4292  | 100     | 0.0329        | -               |
| 0.6438  | 150     | 0.0008        | -               |
| 0.8584  | 200     | 0.0002        | -               |
| **1.0** | **233** | **-**         | **0.1542**      |
| 1.0730  | 250     | 0.0002        | -               |
| 1.2876  | 300     | 0.0001        | -               |
| 1.5021  | 350     | 0.0002        | -               |
| 1.7167  | 400     | 0.0001        | -               |
| 1.9313  | 450     | 0.0001        | -               |
| 2.0     | 466     | -             | 0.1631          |
| 2.1459  | 500     | 0.0001        | -               |
| 2.3605  | 550     | 0.0001        | -               |
| 2.5751  | 600     | 0.0001        | -               |
| 2.7897  | 650     | 0.0001        | -               |
| 3.0     | 699     | -             | 0.1648          |
| 3.0043  | 700     | 0.0001        | -               |
| 3.2189  | 750     | 0.0001        | -               |
| 3.4335  | 800     | 0.0001        | -               |
| 3.6481  | 850     | 0.0001        | -               |
| 3.8627  | 900     | 0.0001        | -               |
| 4.0     | 932     | -             | 0.1663          |
| 4.0773  | 950     | 0.0001        | -               |
| 4.2918  | 1000    | 0.0           | -               |
| 4.5064  | 1050    | 0.0           | -               |
| 4.7210  | 1100    | 0.0001        | -               |
| 4.9356  | 1150    | 0.0001        | -               |
| 5.0     | 1165    | -             | 0.1648          |

* The bold row denotes the saved checkpoint.
### Framework Versions
- Python: 3.9.19
- SetFit: 1.1.0.dev0
- Sentence Transformers: 3.0.1
- Transformers: 4.39.0
- PyTorch: 2.4.0
- Datasets: 2.20.0
- Tokenizers: 0.15.2

## 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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