visolex/phobert-spam-classification
022
PhoBERT-Spam-MultiClass
Fine-tuned from `vinai/phobert-base` on ViSpamReviews (multi-class).
- Task: 4-way classification
- Dataset: ViSpamReviews
- Hyperparameters
- Batch size: 32
- LR: 3e-5
- Epochs: 100
- Max seq len: 256
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("visolex/phobert-spam-classification")
model = AutoModelForSequenceClassification.from_pretrained("visolex/phobert-spam-classification")
text = "Chỉ PR thương hiệu chứ không review thật."
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=256)
pred = model(**inputs).logits.argmax(dim=-1).item()
label_map = {0: "NO-SPAM",1: "SPAM-1",2: "SPAM-2",3: "SPAM-3"}
print(label_map[pred])