Fine-Tuning LLMs for Math Reasoning While Preserving Safety Alignment

Fine-tuned Qwen2.5 model(1.5B & 7B) on GSM8K dataset using LoRA, improving math accuracy to 0.81 while maintaining 0.88 safety alignment score on AILuminate Safety Dataset, surpassing baselines.

Performed ablation studies across 10 different hyperparameter configurations (learning rate, LoRA rank, dropout) to analyze performance trade-offs and mitigate catastrophic forgetting in fine-tuned models.

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