Upload stop_overfit_monitor.py

stop_overfit_monitor.py

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+# ==============================================================================
+# COPYRIGHT (C) 2025 KONSTANTIN VLADIMIROVICH GRABKO. ALL RIGHTS RESERVED.
+# PATENT PENDING | CMS MANHATTAN JIRACK TECHNOLOGY
+#
+# This software is licensed under the Commercial License Agreement V.1.2.
+# Any use, modification, or distribution of this code requires compliance with 
+# the terms found in the LICENSE.md file in the root directory.
+#
+# NO PATENTING RIGHTS: Users are strictly prohibited from filing patent claims
+# based on the BRE or SWA architectures disclosed herein.
+# Contact: grabko@cmsmanhattan.com | +1 (516) 777-0945
+# ==============================================================================
+
+# Overfitting & Drift Monitor for Ternary Models
+
+import json
+import os
+import time
+import matplotlib.pyplot as plt
+
+LOG_FILE = "val_metrics_cms.json"
+STOP_LOSS_THRESHOLD = 0.5  # Если разрыв между Pile и Cultural лоссом больше этого значения
+
+def analyze_progress():
+    if not os.path.exists(LOG_FILE):
+        print(">>> Waiting for log file...")
+        return
+
+    with open(LOG_FILE, 'r') as f:
+        data = json.load(f)
+
+    if len(data) < 2:
+        return
+
+    steps = [int(d['step']) for d in data]
+    p_loss = [d['pile_loss'] for d in data]
+    c_loss = [d['cultural_loss'] for d in data]
+    
+    # Расчет разрыва (Gap)
+    gap = p_loss[-1] - c_loss[-1]
+    
+    print(f"\n--- CMS Status Check (Step {steps[-1]}) ---")
+    print(f"Pile Loss: {p_loss[-1]:.4f}")
+    print(f"Cultural Loss: {c_loss[-1]:.4f}")
+    print(f"Current Gap: {gap:.4f}")
+
+    # Логика предупреждений
+    if gap > STOP_LOSS_THRESHOLD:
+        print("⚠️ WARNING: Overfitting detected! Model is focusing too much on Cultural Code.")
+        print(">>> Recommendation: Reduce MIX_RATIO or stop training soon.")
+    elif gap < 0:
+        print("ℹ️ INFO: Model is still learning basic language better than your specific data.")
+        print(">>> Recommendation: Increase MIX_RATIO for faster adaptation.")
+    else:
+        print("✅ STATUS: Healthy training. General and specific knowledge are balancing.")
+
+    # Генерация графика
+    plt.figure(figsize=(10, 5))
+    plt.plot(steps, p_loss, label='General Knowledge (Pile)', color='blue', marker='o')
+    plt.plot(steps, c_loss, label='Cultural Code (Client)', color='green', marker='s')
+    plt.axhline(y=min(c_loss), color='r', linestyle='--', alpha=0.3)
+    plt.xlabel('Training Steps')
+    plt.ylabel('Loss')
+    plt.title('CMS Manhattan: Training Convergence')
+    plt.legend()
+    plt.grid(True)
+    plt.savefig('training_progress.png')
+    plt.close()
+    print(">>> Progress chart updated: training_progress.png")
+
+if __name__ == "__main__":
+    print(">>> CMS Overfit Monitor active.")
+    while True:
+        analyze_progress()
+        time.sleep(300) # Проверка каждые 5 минут