Update README.md

README.md

@@ -24,7 +24,7 @@ LLMSIEM/logem is a specialized language model fine-tuned for Security Informatio
 
 LLMSIEM/logem is a fine-tuned version of Qwen3-0.6B, specifically optimized for cybersecurity applications. The model demonstrates that targeted fine-tuning can dramatically improve performance on domain-specific tasks, achieving superior results compared to much larger general-purpose models.
 
-- **Developed by:** [Your Name/Organization]
+- **Developed by:** [Hassan Shehata]
 - **Model type:** Causal Language Model (Fine-tuned)
 - **Language(s):** English
 - **License:** Apache 2.0
@@ -34,8 +34,6 @@ LLMSIEM/logem is a fine-tuned version of Qwen3-0.6B, specifically optimized for
 
 ### Model Sources
 
-- **Repository:** [Your GitHub Repository]
-- **Paper:** [Research Paper Link if available]
 - **Blog Post:** [LinkedIn/Blog Series Link]
 
 ## Performance Highlights
@@ -206,7 +204,7 @@ Dataset characteristics:
 
 Training a specialized 0.6B parameter model requires significantly less computational resources compared to training larger models from scratch:
 
-- **Hardware Type:** NVIDIA GPU (specific details TBD)
+- **Hardware Type:** NVIDIA GPU (RTX3060)
 - **Training approach:** Fine-tuning (more efficient than training from scratch)
 - **Base model efficiency:** Starting from pre-trained Qwen3-0.6B reduces carbon footprint
 - **Production efficiency:** Smaller model size reduces inference energy consumption