Tina: Tiny Reasoning Models via LoRA

Tina is the family of models created by post-training the DeepSeek-R1-Distill-Qwen-1.5B base model using low-rank adaptation (LoRA) during reinforcement learning (RL), on open-source reasoning datasets.

• Paper: https://arxiv.org/abs/2504.15777
• Notion Blog: https://shangshangwang.notion.site/tina
• Code Repository: https://github.com/shangshang-wang/Tina
• Training Logs: https://wandb.ai/upup-ashton-wang-usc/Tina

Tina's avatar is generated by GPT-4o based on KYNE's girls and the following prompt.

Hi, I’m Tina — an INTJ who’s all about getting to the essence of things. I study reasoning models because I’m fascinated by how structured thinking and logic can emerge from data. Outside of that, I recharge with movies, music, and the occasional gaming session. I believe in strategic effort: minimal input, maximum impact — whether it’s in research or everyday life, I’m always looking for the most efficient path to meaningful results.