thai-sentiment-phayabert

Thai Sentiment Analysis - PhayaThaiBERT

Fine-tuned PhayaThaiBERT for Thai sentiment classification.

Model Details

• Base Model: PhayaThaiBERT (110M parameters)
• Task: 3-class sentiment (positive/neutral/negative)
• Dataset: Wisesight Sentiment (21k training samples)
• Performance: 82% accuracy, 0.81 weighted F1

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model = AutoModelForSequenceClassification.from_pretrained("yourusername/thai-sentiment-phayabert")
tokenizer = AutoTokenizer.from_pretrained("yourusername/thai-sentiment-phayabert")

text = "อาหารอร่อยมาก"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
prediction = torch.argmax(outputs.logits, dim=-1).item()

labels = {0: "positive", 1: "neutral", 2: "negative"}
print(labels[prediction])  # positive