Update README.md

README.md

@@ -25,21 +25,21 @@ language:
 - vi
 - yo
 base_model:
-- Qwen/Qwen2.5-7B-Instruct
+- Qwen/Qwen2.5-3B-Instruct
 pipeline_tag: text-generation
 ---
 
 # Model Card for Model ID
 
-CURE-MED-3B is a 7 billion parameter large language model specialized for multilingual medical reasoning, fine-tuned from Qwen/Qwen2.5-7B using a
+CURE-MED-3B is a 3 billion parameter large language model specialized for multilingual medical reasoning, fine-tuned from Qwen/Qwen2.5-7B using a
 curriculum-informed reinforcement learning framework to enhance logical correctness and language stability in healthcare applications.
 
 
 
 ## Model Details
 
-CURE-MED-7B is part of the CURE-MED family of models, designed to address the challenges of multilingual medical reasoning in large language models (LLMs).
-Built on the Qwen2.5-7B base model, it incorporates a curriculum-informed reinforcement learning approach that integrates code-switching-aware supervised fine-tuning (SFT)
+CURE-MED-3B is part of the CURE-MED family of models, designed to address the challenges of multilingual medical reasoning in large language models (LLMs).
+Built on the Qwen2.5-3B-instruct model, it incorporates a curriculum-informed reinforcement learning approach that integrates code-switching-aware supervised fine-tuning (SFT)
 and Group Relative Policy Optimization (GRPO) to improve performance on open-ended medical queries across 13 languages, including underrepresented ones such as Amharic, Yoruba, and Swahili.
 The model is trained and evaluated using CUREMED-BENCH, a high-quality multilingual open-ended medical reasoning benchmark with single verifiable answers.