⚖️ Legal Document Category Classification Model
📌 Model Details
- Developed by: M SAJAWAL ABBAS
- Model Type: Fine-tuned Transformer for Multi-Class Text Classification
- Base Architecture:
distilbert-base-uncased - Language: English (en)
🎯 Intended Use
Classifies legal texts into 4 primary functional categories:
- Civil / Constitutional Law (ID: 0)
- Criminal Law / Procedure (ID: 1)
- Business / Corporate Law (ID: 2)
- Regulatory / Administrative Law (ID: 3)
📊 Dataset & Training Details
- Dataset:
lex_glue(SCOTUS subset) - Framework: PyTorch & Hugging Face Transformers
- Epochs: 3 | Batch Size: 16 | Learning Rate: 2e-5
👤 Author Metadata
- Author: M SAJAWAL ABBAS
- Environment: Google Colab (GPU) & Hugging Face Hub
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