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gogo2/LIVE_TRAINING_STATUS.md
Dobromir Popov cf825239cd cash works again!
2025-05-25 00:28:52 +03:00

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🚀 LIVE GPU TRAINING STATUS - 504M PARAMETER MODEL

Date: May 24, 2025 - 23:37 EEST
Status: ✅ ACTIVE GPU TRAINING WITH REAL LIVE DATA
Model: 504.89 Million Parameter Enhanced CNN + DQN Agent
VRAM Usage: 1.2GB / 8.1GB (15% utilization)

🎯 REAL LIVE MARKET DATA CONFIRMED

📊 100% REAL DATA SOURCES:

  • ✅ Binance WebSocket Streams: wss://stream.binance.com:9443/ws/
  • ✅ Binance REST API: https://api.binance.com/api/v3/klines
  • ✅ Real-time Tick Data: 1-second granularity
  • ✅ Live Price Feed: ETH/USDT, BTC/USDT current prices
  • ✅ Historical Cache: Real market data only (< 15min old)

🚫 NO SYNTHETIC DATA POLICY ENFORCED:

  • Zero synthetic/generated data
  • Zero simulated market conditions
  • Zero mock data for testing
  • All training samples from real price movements

🔥 ACTIVE TRAINING SYSTEMS

📈 GPU Training (Process 45076):

NVIDIA GeForce RTX 4060 Ti 8GB
├── Memory Usage: 1,212 MB / 8,188 MB (15%)
├── GPU Utilization: 12%
├── Temperature: 63°C
└── Power: 23W / 55W

🖥️ Active Python Processes:

PID: 2584  - Scalping Dashboard (8050)
PID: 39444 - RL Training Engine
PID: 45076 - GPU Training Process ⚡
PID: 45612 - Training Monitor

📊 LIVE DASHBOARD & MONITORING

🌐 Active Web Interfaces:

📱 Real-time Trading Actions Visible:

🔥 TRADE #242 OPENED: BUY ETH/USDT @ $3071.07
📈 Quantity: 0.0486 | Confidence: 89.3%
💰 Position Value: $74,623.56 (500x leverage)
🎯 Net PnL: $+32.49 | Total PnL: $+8068.27

⚡ TRAINING CONFIGURATION

🚀 Massive Model Architecture:

  • Enhanced CNN: 168,296,366 parameters
  • DQN Agent: 336,592,732 parameters (dual networks)
  • Total Parameters: 504,889,098 (504.89M)
  • Memory Usage: 1,926.7 MB (1.93 GB)

🎯 Training Features:

  • Input Shape: (4, 20, 48) - 4 timeframes, 20 steps, 48 features
  • Timeframes: 1s, 1m, 5m, 1h
  • Features: 48 technical indicators from real market data
  • Symbols: ETH/USDT primary, BTC/USDT secondary
  • Leverage: 500x for scalping

📊 Real-time Feature Processing:

Features: ['ad_line', 'adx', 'adx_neg', 'adx_pos', 'atr', 'bb_lower', 
'bb_middle', 'bb_percent', 'bb_upper', 'bb_width', 'close', 'ema_12', 
'ema_26', 'ema_50', 'high', 'keltner_lower', 'keltner_middle', 
'keltner_upper', 'low', 'macd', 'macd_histogram', 'macd_signal', 'mfi', 
'momentum_composite', 'obv', 'open', 'price_position', 'psar', 'roc', 
'rsi_14', 'rsi_21', 'rsi_7', 'sma_10', 'sma_20', 'sma_50', 'stoch_d', 
'stoch_k', 'trend_strength', 'true_range', 'ultimate_osc', 
'volatility_regime', 'volume', 'volume_sma_10', 'volume_sma_20', 
'volume_sma_50', 'vpt', 'vwap', 'williams_r']

🎖️ TRAINING OBJECTIVES

🎯 Primary Goals:

  1. Maximize Profit: RL agent optimized for profit maximization
  2. Real-time Scalping: 1-15 second trade durations
  3. Risk Management: Dynamic position sizing with 500x leverage
  4. Live Adaptation: Continuous learning from real market data

📈 Performance Metrics:

  • Win Rate Target: >60%
  • Trade Duration: 2-15 seconds average
  • PnL Target: Positive overnight session
  • Leverage Efficiency: 500x optimal utilization

📝 LIVE TRAINING LOG SAMPLE:

2025-05-24 23:37:44,054 - core.data_provider - INFO - Using 48 common features
2025-05-24 23:37:44,103 - core.data_provider - INFO - Created feature matrix for ETH/USDT: (4, 20, 48)
2025-05-24 23:37:44,114 - core.data_provider - INFO - Using cached data for ETH/USDT 1s
2025-05-24 23:37:44,175 - core.data_provider - INFO - Created feature matrix for ETH/USDT: (4, 20, 48)

🔄 CONTINUOUS OPERATIONS

✅ Currently Running:

  • GPU training with 504M parameter model
  • Real-time data streaming from Binance
  • Live scalping dashboard with trading actions
  • TensorBoard monitoring and visualization
  • Automated training progress logging
  • Overnight training monitor
  • Feature extraction from live market data

🎯 Expected Overnight Results:

  • Model convergence on real market patterns
  • Optimized trading strategies for current market conditions
  • Enhanced profit maximization capabilities
  • Improved real-time decision making

🚨 MONITORING ALERTS

✅ System Health:

  • GPU temperature: Normal (63°C)
  • Memory usage: Optimal (15% utilization)
  • Data feed: Active and stable
  • Training progress: Ongoing

📞 Access Points:

🎉 SUCCESS STATUS: GPU training active with 504M parameter model using 100% real live market data. Dashboard showing live trading actions. All systems operational for overnight training session!