gincioks/smartshot-zeroshot-finetuned-v0.2.0

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

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