You can deploy this model and start earning money today!

luis-espinosa/
gte-small_lc_summs_setfit

Name: gte-small_lc_summs_setfit
Availability: InStock

setfit

safetensors

bert

sentence-transformers

text-classification

generated_from_setfit_trainer

2209.11055

thenlper/gte-small

finetune

Views

No views yet

SetFit with thenlper/gte-small

This is a SetFit model that can be used for Text Classification. This SetFit model uses thenlper/gte-small as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.

The model has been trained using an efficient few-shot learning technique that involves:

Fine-tuning a Sentence Transformer with contrastive learning.
Training a classification head with features from the fine-tuned Sentence Transformer.

Model Details

Model Description

Model Type: SetFit
Sentence Transformer body: thenlper/gte-small
Classification head: a LogisticRegression instance
Maximum Sequence Length: 512 tokens
Number of Classes: 2 classes

Model Sources

Repository: SetFit on GitHub
Paper: Efficient Few-Shot Learning Without Prompts
Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts

Model Labels

Label

Examples

'Wentworth will become Walgreens CEO effective Oct. 23 . He is the former CEO of Express Scripts, the pharmacy benefit manager acquired by Cigna in 2018 .'
'CVS Health announces CFO Shawn Guertin to take leave of absence . Senior Vice President of Corporate Finance, Tom Cowhey, has been appointed interim CFO . CEO of Oak Street Health Mike Pykosz has been named interim President of Health Services .'
'Walgreens Boots Alliance Inc. appointed Tim Wentworth as its next chief executive officer . The former CEO of pharmacy-benefits manager Express Scripts succeeds Rosalind Brewer, a longtime retail executive whose 2 1/2-year tenure saw the shares lose half their value .'

"Dove's Milk Chocolate Tiramisu Caramel Promises is debuting a new addition to its Promises line of sweets . Inspired by the Italian dessert, the candy features a tiramisu-flavored caramel center that is surrounded by milk chocolate . The new flavor features fried dough flavored cookies with a churro flavored crème ."
"Walgreens' 'non-drowsy' cough meds are anything but, lawsuit claims $3B project with AbilityLab's Detroit outpost breaks ground this spring There's a battle underway over medication abortion, the most common method of terminating a pregnancy in the US . The Supreme Court is scheduled to hear arguments on March 26 in a case that will determine how available mifepristone will be . It would also open the door to challenges to other FDA decisions ."
'CVS Health invests more than $3M to improve health outcomes in Phoenix Terms of use Photo and video available via the CVS health Newsroom are for'

Uses

Direct Use for Inference

First install the SetFit library:

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("luis-espinosa/gte-small_lc_summs_setfit")
# Run inference
preds = model("Wentworth will become Walgreens CEO effective Oct. 23 . He is the former CEO of Express Scripts, the pharmacy benefit manager acquired by Cigna in 2018 .")

Training Details

Training Set Metrics

Training set	Min	Median	Max
Word count	26	52.6190	80

Label	Training Sample Count
0	11
1	10

Training Hyperparameters

batch_size: (16, 16)
num_epochs: (3, 3)
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
0.0189	1	0.3391	-
0.9434	50	0.0106	-
1.8868	100	0.001	-
2.8302	150	0.0005	-

Framework Versions

Python: 3.10.12
SetFit: 1.0.3
Sentence Transformers: 3.0.1
Transformers: 4.41.2
PyTorch: 2.3.1+cu121
Datasets: 2.19.2
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}
}