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Is New Dataset Teacher Model

Developed by librarian-bots
A few-shot learning text classification model based on the SetFit framework, achieving efficient classification through contrastive learning and classification head training
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Release Time : 10/5/2023

Model Overview

This model is trained using the SetFit framework, combining Sentence Transformer's contrastive learning and classification head training techniques, suitable for text classification tasks in few-shot scenarios.

Model Features

Few-shot Learning
Achieves efficient few-shot learning through the SetFit framework, performing excellently with limited data
Two-stage Training
First fine-tunes Sentence Transformer through contrastive learning, then trains the classification head to enhance model performance
No Prompt Engineering
Uses the SetFit method, avoiding complex prompt engineering in traditional few-shot learning

Model Capabilities

Text Classification
Few-shot Learning

Use Cases

Content Classification
Sentiment Analysis
Classifies sentiment tendencies in user comments
Topic Classification
Classifies topics in news or articles
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