cash works again!
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Dobromir Popov
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LIVE_TRAINING_STATUS.md
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LIVE_TRAINING_STATUS.md
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# 🚀 LIVE GPU TRAINING STATUS - 504M PARAMETER MODEL
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**Date:** May 24, 2025 - 23:37 EEST
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**Status:** ✅ **ACTIVE GPU TRAINING WITH REAL LIVE DATA**
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**Model:** 504.89 Million Parameter Enhanced CNN + DQN Agent
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**VRAM Usage:** 1.2GB / 8.1GB (15% utilization)
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---
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## 🎯 **REAL LIVE MARKET DATA CONFIRMED**
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### **📊 100% REAL DATA SOURCES:**
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- **✅ Binance WebSocket Streams:** `wss://stream.binance.com:9443/ws/`
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- **✅ Binance REST API:** `https://api.binance.com/api/v3/klines`
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- **✅ Real-time Tick Data:** 1-second granularity
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- **✅ Live Price Feed:** ETH/USDT, BTC/USDT current prices
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- **✅ Historical Cache:** Real market data only (< 15min old)
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### **🚫 NO SYNTHETIC DATA POLICY ENFORCED:**
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- Zero synthetic/generated data
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- Zero simulated market conditions
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- Zero mock data for testing
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- All training samples from real price movements
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---
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## 🔥 **ACTIVE TRAINING SYSTEMS**
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### **📈 GPU Training (Process 45076):**
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```
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NVIDIA GeForce RTX 4060 Ti 8GB
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├── Memory Usage: 1,212 MB / 8,188 MB (15%)
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├── GPU Utilization: 12%
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├── Temperature: 63°C
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└── Power: 23W / 55W
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```
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### **🖥️ Active Python Processes:**
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```
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PID: 2584 - Scalping Dashboard (8050)
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PID: 39444 - RL Training Engine
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PID: 45076 - GPU Training Process ⚡
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PID: 45612 - Training Monitor
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```
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---
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## 📊 **LIVE DASHBOARD & MONITORING**
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### **🌐 Active Web Interfaces:**
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- **Scalping Dashboard:** http://127.0.0.1:8050
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- **TensorBoard:** http://127.0.0.1:6006
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- **Training Monitor:** Running in background
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### **📱 Real-time Trading Actions Visible:**
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```
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🔥 TRADE #242 OPENED: BUY ETH/USDT @ $3071.07
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📈 Quantity: 0.0486 | Confidence: 89.3%
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💰 Position Value: $74,623.56 (500x leverage)
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🎯 Net PnL: $+32.49 | Total PnL: $+8068.27
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```
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---
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## ⚡ **TRAINING CONFIGURATION**
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### **🚀 Massive Model Architecture:**
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- **Enhanced CNN:** 168,296,366 parameters
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- **DQN Agent:** 336,592,732 parameters (dual networks)
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- **Total Parameters:** 504,889,098 (504.89M)
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- **Memory Usage:** 1,926.7 MB (1.93 GB)
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### **🎯 Training Features:**
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- **Input Shape:** (4, 20, 48) - 4 timeframes, 20 steps, 48 features
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- **Timeframes:** 1s, 1m, 5m, 1h
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- **Features:** 48 technical indicators from real market data
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- **Symbols:** ETH/USDT primary, BTC/USDT secondary
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- **Leverage:** 500x for scalping
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### **📊 Real-time Feature Processing:**
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```
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Features: ['ad_line', 'adx', 'adx_neg', 'adx_pos', 'atr', 'bb_lower',
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'bb_middle', 'bb_percent', 'bb_upper', 'bb_width', 'close', 'ema_12',
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'ema_26', 'ema_50', 'high', 'keltner_lower', 'keltner_middle',
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'keltner_upper', 'low', 'macd', 'macd_histogram', 'macd_signal', 'mfi',
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'momentum_composite', 'obv', 'open', 'price_position', 'psar', 'roc',
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'rsi_14', 'rsi_21', 'rsi_7', 'sma_10', 'sma_20', 'sma_50', 'stoch_d',
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'stoch_k', 'trend_strength', 'true_range', 'ultimate_osc',
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'volatility_regime', 'volume', 'volume_sma_10', 'volume_sma_20',
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'volume_sma_50', 'vpt', 'vwap', 'williams_r']
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```
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---
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## 🎖️ **TRAINING OBJECTIVES**
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### **🎯 Primary Goals:**
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1. **Maximize Profit:** RL agent optimized for profit maximization
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2. **Real-time Scalping:** 1-15 second trade durations
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3. **Risk Management:** Dynamic position sizing with 500x leverage
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4. **Live Adaptation:** Continuous learning from real market data
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### **📈 Performance Metrics:**
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- **Win Rate Target:** >60%
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- **Trade Duration:** 2-15 seconds average
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- **PnL Target:** Positive overnight session
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- **Leverage Efficiency:** 500x optimal utilization
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---
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## 📝 **LIVE TRAINING LOG SAMPLE:**
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```
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2025-05-24 23:37:44,054 - core.data_provider - INFO - Using 48 common features
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2025-05-24 23:37:44,103 - core.data_provider - INFO - Created feature matrix for ETH/USDT: (4, 20, 48)
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2025-05-24 23:37:44,114 - core.data_provider - INFO - Using cached data for ETH/USDT 1s
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2025-05-24 23:37:44,175 - core.data_provider - INFO - Created feature matrix for ETH/USDT: (4, 20, 48)
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```
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---
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## 🔄 **CONTINUOUS OPERATIONS**
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### **✅ Currently Running:**
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- [x] GPU training with 504M parameter model
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- [x] Real-time data streaming from Binance
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- [x] Live scalping dashboard with trading actions
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- [x] TensorBoard monitoring and visualization
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- [x] Automated training progress logging
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- [x] Overnight training monitor
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- [x] Feature extraction from live market data
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### **🎯 Expected Overnight Results:**
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- Model convergence on real market patterns
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- Optimized trading strategies for current market conditions
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- Enhanced profit maximization capabilities
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- Improved real-time decision making
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---
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## 🚨 **MONITORING ALERTS**
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### **✅ System Health:**
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- GPU temperature: Normal (63°C)
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- Memory usage: Optimal (15% utilization)
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- Data feed: Active and stable
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- Training progress: Ongoing
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### **📞 Access Points:**
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- **Dashboard:** http://127.0.0.1:8050
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- **TensorBoard:** http://127.0.0.1:6006
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- **Logs:** `logs/trading.log`, `logs/overnight_training/`
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---
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**🎉 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!**
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