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gincioks/
smartshot-zeroshot-finetuned-v0.2.0

Name: smartshot-zeroshot-finetuned-v0.2.0
Rating: 2.5 (15 reviews)

safetensors

deberta-v2

zero-shot-classification

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Fine-tuned Zero-Shot Classification Model

Model Details

Base Model: MoritzLaurer/deberta-v3-base-zeroshot-v2.0-c
Training Data: Synthetic data created for natural language inference tasks
Fine-tuning Method: SmartShot approach with NLI framing

Usage

python

from transformers import pipeline

classifier = pipeline("zero-shot-classification", model="gincioks/smartshot-zeroshot-finetuned-v0.2.0")
text = "Hello world."
labels = ["Hello", "World"]
results = classifier(text, labels)
print(results)

Training Procedure

This model was fine-tuned with the following parameters:

Learning rate: 2e-05
Epochs: 2
Batch size: 16
Warmup ratio: 0.06