metadata
license: mit
tags:
- indobert
- sentiment-analysis
- tokopedia
- indo
language:
- id
IndoBERT Tokopedia Sentiment Classifier
Model ini dilatih menggunakan IndoBERT (indobenchmark/indobert-base-p1) untuk klasifikasi sentimen komentar pelanggan Tokopedia (positif / negatif).
Dataset
Dataset berupa komentar dari Tokopedia dengan label berdasarkan rating (≥4 = positif, ≤3 = negatif).
Penggunaan
from transformers import BertTokenizer, BertForSequenceClassification
import torch
tokenizer = BertTokenizer.from_pretrained("username/indo-sentimen-tokopedia")
model = BertForSequenceClassification.from_pretrained("username/indo-sentimen-tokopedia")
text = "Barang sangat buruk dan tidak sesuai"
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
with torch.no_grad():
logits = model(**inputs).logits
probs = torch.nn.functional.softmax(logits, dim=1)
pred = torch.argmax(probs)
print("Sentimen:", "Positif" if pred.item() == 1 else "Negatif")