sanvo/vietnamese-sentiment-phobert

Vietnamese Sentiment Analysis with PhoBERT

Fine-tuned VinAI/PhoBERT-base for 3-class sentiment classification on Vietnamese product reviews.

Model Description

This model classifies Vietnamese text into three sentiment categories:

• Positive (tích cực)
• Neutral (trung lập)
• Negative (tiêu cực)

Training Data

• 10,000+ Vietnamese product reviews
• Balanced across 3 sentiment classes
• Preprocessed with Vietnamese word segmentation

Performance

Metric	Score
Accuracy	85%
F1-Score (weighted)	0.84

Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="sanvo/vietnamese-sentiment-phobert")
result = classifier("Sản phẩm rất tốt, tôi rất hài lòng")
print(result)

Training Details

• Base model: vinai/phobert-base
• Epochs: 5
• Batch size: 16
• Learning rate: 2e-5
• Max length: 256 tokens
• Optimizer: AdamW with linear warmup