metadata
language: th
license: apache-2.0
tags:
- sentiment-analysis
- thai
- youtube-comments
- bert
library_name: transformers
pipeline_tag: text-classification
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}
}