Update README.md

README.md

@@ -26,13 +26,14 @@ The model emphasizes **reasoning quality, instruction robustness, and stability
 - 16K context length  
 - Optimized for reasoning-centric tasks  
 - Designed for modern GPU inference runtimes  
-- **Architecture:** Qwen3-compatible (DeepBrainz-R series, optimized via OPD)
+- **Architecture:** Qwen3-compatible (DeepBrainz-R series, post-trained, and optimized for math and coding)
 
 ---
 
 ## Intended Use
 
-- Advanced reasoning systems  
+- Advanced reasoning systems
+- Math and Coding
 - Research and evaluation  
 - Agentic workflows  
 - Inference-time scaling and test-time compute experiments  
@@ -69,7 +70,7 @@ print(tok.decode(out[0], skip_special_tokens=True))
 
 ## Training Summary
 
-The model was produced using a **multi-stage optimization process** involving large-scale supervision and **iterative refinement** to improve reasoning quality and robustness.
+The model was produced using a **multi-stage optimization process** involving large-scale on-policy optimization and **iterative refinement** to improve reasoning quality and robustness.
 
 Specific training details are intentionally abstracted in this public release.