metadata
language: th
license: mit
tags:
- sentiment-analysis
- thai
- phayathaibert
datasets:
- wisesight_sentiment
metrics:
- accuracy
- f1
model-index:
- name: thai-sentiment-phayabert
results:
- task:
type: text-classification
dataset:
name: wisesight_sentiment
type: wisesight_sentiment
metrics:
- type: accuracy
value: 0.82
- type: f1
value: 0.81
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