vietkq1/vietnamese-sentiment-phobert

🇻🇳 Vietnamese Sentiment Analysis (PhoBERT)

This is a fine-tuned version of vinai/phobert-base for sentiment analysis on Vietnamese text.
It was trained to classify user reviews or text inputs into either:

• POSITIVE (1)
• NEGATIVE (0)

🔧 Model Details

• Base model: vinai/phobert-base
• Fine-tuned by: vietkq1
• Language: Vietnamese (vi)
• Task: Sentiment Analysis (text-classification)
• Framework: HuggingFace Transformers + PyTorch

🧠 Intended Uses

This model is ideal for:

• Classifying reviews (e.g., app reviews, product reviews, etc.)
• Analyzing user feedback in Vietnamese
• Social media sentiment mining

🧪 Example Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
from transformers import pipeline

model = AutoModelForSequenceClassification.from_pretrained("vietkq1/vietnamese-sentiment-phobert")
tokenizer = AutoTokenizer.from_pretrained("vietkq1/vietnamese-sentiment-phobert")

classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)

text = "Sản phẩm quá tuyệt vời, mình rất hài lòng!"
print(classifier(text))