phobert-v2-hsd-span: Hate Speech Span Detection (Vietnamese)

This model is a fine-tuned version of phobert-v2 for Vietnamese Hate Speech Span Detection.

Model Details

• Base Model: phobert-v2
• Description: Vietnamese Hate Speech Span Detection
• Framework: HuggingFace Transformers
• Task: Hate Speech Span Detection (token/char-level spans)

Hyperparameters

• Max sequence length: 64
• Learning rate: 5e-6
• Batch size: 32
• Epochs: 100
• Early stopping patience: 5

Results

• F1: 0.6326
• Precision: 0.6494
• Recall: 0.6305
• Exact Match: 0.0000

Usage

from transformers import AutoTokenizer, AutoModelForTokenClassification
import torch

model_name = "phobert-v2-hsd-span"
tok = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForTokenClassification.from_pretrained(model_name)
text = "Ví dụ câu tiếng Việt có nội dung thù ghét ..."
enc = tok(text, return_tensors="pt", truncation=True, max_length=256, is_split_into_words=False)
with torch.no_grad():
    logits = model(**enc).logits
    pred_ids = logits.argmax(-1)[0].tolist()
# TODO: chuyển pred_ids -> spans theo scheme nhãn của bạn (BIO/BILOU/char-offset)

License

Apache-2.0

Acknowledgments

• Base model: phobert-v2