Update README.md

README.md

@@ -70,22 +70,17 @@ task_categories:
 The model predicts ionic stability and simulated quantum state transitions in ionic environments. Trapped-ion quantum simulators, typically involve physical hardware for tasks like 
 entanglement measurement or Hamiltonian engineering. This dataset is desgined as a fully synthetic browser-based alternative for developers without lab access. 
 
-### SPECS
 
 **Model Name:** IonicOceanSyntheticDataset_v7.0
 **Version:** 7.0
 **Export Date:** 2025-12-31T00:27:29.944Z
 
-### Training Summary
-
 - **Total Epochs:** 3
 - **Final Loss:** 0.6713
 - **Final Accuracy:** 65.6%
 - **Training Samples:** 800
 - **Simulation Time:** 37.8s
 
-### Dataset Information
-
 This package contains real-time captured data from the ionic ocean simulation:
 
 **Particle Data:**
@@ -101,6 +96,7 @@ This package contains real-time captured data from the ionic ocean simulation:
 4. Model state - neural network parameters at capture time
 
 ### Model Architecture
+
 ```
 Input(5) → Dense(32, relu) → Dropout(0.2)
          → Dense(16, relu)
@@ -125,6 +121,7 @@ Input(5) → Dense(32, relu) → Dropout(0.2)
 - **Target FPS:** 60
 
 ### File Structure
+
 ```
 ionicsphere_export_v7.0_*.zip/
 ├── model_metadata.json     # Model configuration and stats
@@ -134,6 +131,7 @@ ionicsphere_export_v7.0_*.zip/
 ├── terminal_log.txt       # CLI interaction history
 └── config.json           # System configuration
 ```
+
 ### Theory
 
 The Ionic Ocean Synthetic Dataset is a specialized dataset designed to bridge the gap between complex atmospheric physics and efficient machine learning models.