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language: en
license: mit
tags:
- sentiment-analysis
- cybersecurity
- bert
widget:
- text: "Security team successfully prevents major data breach"
example_title: "Positive"
- text: "Ransomware attack shuts down hospital systems"
example_title: "Negative"
- text: "New security guidelines published by agency"
example_title: "Neutral"
---
# Security Sentiment Analyzer
Fine-tuned BERT model that analyzes sentiment of cybersecurity news headlines.
## Model Details
- **Base Model:** `bert-base-uncased`
- **Task:** Text Classification (Sentiment Analysis)
- **Labels:**
- `0`: Positive 🟢
- `1`: Negative 🔴
- `2`: Neutral 🔵
## Accuracy
**87.5%** on test set
## How to Use
```python
from transformers import pipeline
classifier = pipeline("text-classification", model="Aikaksh-Singh-Routela/security-sentiment-model")
result = classifier("Ransomware attack shuts down hospital systems")
print(result)
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