MrPanuwit/thai-youtube-sentiment-subtask2

Model Description

Thai sentiment analysis model trained on YouTube comments for comment category classification.

Model Details

• Model Type: BERT-based text classification
• Language: Thai (th)
• Task: comment category classification
• Base Model: bert-base-multilingual-cased
• Training Data: YouTube comments dataset

Labels

• Appreciation
• Criticism
• Offensive
• Suggestion
• nan

Usage

from transformers import BertTokenizer, BertForSequenceClassification
import torch

# Load model and tokenizer
tokenizer = BertTokenizer.from_pretrained("MrPanuwit/thai-youtube-sentiment-subtask2")
model = BertForSequenceClassification.from_pretrained("MrPanuwit/thai-youtube-sentiment-subtask2")

# Example usage
text = "วิดีโอนี้สนุกมาก"
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=128)

with torch.no_grad():
    outputs = model(**inputs)
    predictions = torch.argmax(outputs.logits, dim=-1)
    
print(f"Prediction: {predictions.item()}")

Training Details

• Framework: PyTorch + Transformers
• Optimizer: AdamW
• Max Sequence Length: 128

Limitations

• Trained specifically on Thai YouTube comments
• May not perform well on other text domains
• Limited to the specific sentiment categories in training data

Citation

@misc{thai-youtube-sentiment,
  author = {Your Name},
  title = {Thai YouTube Comment Sentiment Analysis},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/MrPanuwit/thai-youtube-sentiment-subtask2}
}