Political Concept Classifier (Phi-3 LoRA)
A LoRA-fine-tuned Phi-3 model for classifying political text excerpts into key concepts. This model is designed to help analyze political content in articles, speeches, social media, or other text sources.
Model Overview
Base model: Phi-3
Fine-tuning method: LoRA (Low-Rank Adaptation)
Task: Text classification
Concepts:
- Economy
- Immigration
- Healthcare
- [Additional categories if applicable]
This model predicts the most relevant political concept for a given text input.
Intended Use
- Research and analysis of political text.
- Classifying statements, articles, or reports according to key political topics.
- Supporting journalists, analysts, or educators in understanding political content trends.
Limitations
- Predictions are dependent on the training dataset and may misclassify ambiguous or out-of-domain text.
- Designed for analysis purposes; not legal, medical, or policy advice.
- May not capture nuances outside the trained categories.
Training Details
- Fine-tuned with LoRA for efficient adaptation while preserving Phi-3’s pretrained knowledge.
- Trained on a dataset of labeled political text excerpts spanning multiple categories.