README.md

A model fine-tuned for sentiment analysis based on [vinai/phobert-base](https://huggingface.co/vinai/phobert-base).

Labels:
- NEG: Negative
- POS: Positive
- NEU: Neutral

Dataset: Comments on Shoppe (https://shopee.vn/)
## Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

tokenizer = AutoTokenizer.from_pretrained("lamsytan/sentiment-analysis-base-phobert")
model = AutoModelForSequenceClassification.from_pretrained("lamsytan/sentiment-analysis-base-phobert")

sentence = "Áo đẹp lắm nhá lần sau sẽ ghé tiếp ạ"

inputs = tokenizer(sentence, return_tensors="pt", padding=True, truncation=True)

with torch.no_grad():
    outputs = model(**inputs)
    logits = outputs.logits
    probabilities = torch.softmax(logits, dim=-1)

print(probabilities.tolist())
    # Output:
    # [[0.010827462188899517, 0.9538241624832153, 0.035348404198884964]]
    #     ^      ^      ^
    #    NEG    POS    NEU