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Phobert Content 256

Developed by RonTon05
A Vietnamese text classification model fine-tuned from vinai/phobert-base-v2, achieving 89.62% accuracy on the validation set
Downloads 64
Release Time : 4/9/2025

Model Overview

This model is an optimized BERT variant for Vietnamese text content classification tasks, suitable for short text classification scenarios

Model Features

Vietnamese optimization
Based on the PhoBERT architecture specifically designed for Vietnamese, it performs excellently in Vietnamese text processing
Efficient fine-tuning
Fine-tuned for 10 epochs with a learning rate of 2e-5, achieving nearly 90% accuracy on the validation set
Lightweight deployment
Moderate parameter size of the base model makes it suitable for real-world production deployment

Model Capabilities

Vietnamese text classification
Short text content analysis
Multi-category prediction

Use Cases

Content moderation
User-generated content classification
Classifying Vietnamese user comments on social media
89.62% accuracy, 88.69% F1 score
Customer service
Ticket auto-classification
Automatically classifying Vietnamese customer service requests
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