--- license: apache-2.0 datasets: - bharatgenai/BhashaBench-Legal - SnehaDeshmukh/IndianBailJudgments-1200 language: - en - hi base_model: - Qwen/Qwen3-0.6B-Base pipeline_tag: text-generation library_name: transformers tags: - legal - BharatGen - LLM - pytorch - transformer - qwen - law --- ****Qwen-BharatBench-Legal**** Qwen-BharatBench-Legal is a fine-tuned version of Qwen/Qwen3-0.6B-Base for Indian Legal NLP tasks. This model can answer bail judgment outcome questions and multiple-choice legal questions in both English and Hindi. ____________________________________________________________________ Key Features Domain-specific: Trained on real Indian legal judgments + law MCQs. Bilingual: Supports English + Hindi inputs. Compact: Based on Qwen 0.6B — lightweight and efficient for experimentation. LoRA Fine-Tuned: Only ~0.38% of parameters trained → efficient & deployable. ____________________________________________________________________ Training Data SnehaDeshmukh/IndianBailJudgments-1200: Bail outcome prediction dataset. BharatBench-Legal: 24k+ Hindi & English law MCQs covering Contract Law, IPC, Family Law, etc. ____________________________________________________________________ Training Details Base Model: Qwen/Qwen3-0.6B-Base Method: LoRA fine-tuning (PEFT) Epochs: 3 Train Samples: ~25,500 Final Train Loss: ~0.017 ____________________________________________________________________ Intended Use Educational & research purposes in Legal NLP. Legal reasoning experiments in Indian context. Teaching tools for law students. Not a substitute for professional legal advice. ____________________________________________________________________ NOTE: The model may hallucinate or produce incorrect legal outcomes. Always consult a qualified lawyer for real cases. ____________________________________________________________________ Acknowledgments Thanks to BharatGen for this amazing dataset. ____________________________________________________________________ License: Apache 2.0