FinBERT Financial News Sentiment — LoRA Adapter
This repository contains a LoRA (PEFT) adapter fine-tuned for financial news sentiment analysis using the Sentiment Analysis for Financial News (FinancialPhraseBank) dataset.
Labels
- 0: negative
- 1: neutral
- 2: positive
Base model
- ProsusAI/finbert
Usage
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from peft import PeftModel
base_id = "ProsusAI/finbert"
adapter_id = "prithvi1029/finbert-financial-news-lora"
tok = AutoTokenizer.from_pretrained(base_id)
base = AutoModelForSequenceClassification.from_pretrained(
base_id, num_labels=3
)
model = PeftModel.from_pretrained(base, adapter_id)
text = "Company shares surged after strong quarterly earnings."
inputs = tok(text, return_tensors='pt', truncation=True)
with torch.no_grad():
logits = model(**inputs).logits
pred = logits.argmax(-1).item()
print('Prediction:', pred)
Disclaimer
This model is for research and educational purposes only and not financial advice.
Training data
- prithvi1029/sentiment-analysis-for-financial-news