A technical guide details the process of fine-tuning NVIDIA's 8-billion-parameter language model for legal contract analysis. Through six experiments using LoRA and quantization, the model's Macro-F1 score improved from 0.2956 to 0.8246, with exact-match accuracy reaching 91.5%. This fine-tuned model was integrated into NemoCounsel, an AI contract review assistant developed by the RTX Renegades team as part of NVIDIA's India Agentic AI Open Hackathon. AI
IMPACT Demonstrates a practical application of fine-tuning for specialized tasks, potentially improving efficiency in legal document analysis.
RANK_REASON The article describes a fine-tuning process for an existing model and its application in a specific tool, rather than a new model release or significant industry event.
Read on Medium — fine-tuning tag →
- 8-Billion-Parameter Language Model
- Aditya Rallapalli
- Lora
- NemoCounsel
- NVIDIA
- Raghul Asokan
- RTX Renegades
- Ruchita Bhandari
- Sainath Chakravadhanula
- Stuti Chourasia
- Sutanshu Raj
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