scalping dash also works initially
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38
config.yaml
38
config.yaml
@ -99,14 +99,27 @@ training:
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validation_split: 0.2
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early_stopping_patience: 10
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# CNN specific
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cnn_training_interval: 21600 # Train every 6 hours
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min_perfect_moves: 200 # Minimum moves before training
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# CNN specific training
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cnn_training_interval: 3600 # Train CNN every hour (was 6 hours)
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min_perfect_moves: 50 # Reduced from 200 for faster learning
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# RL specific
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rl_training_interval: 3600 # Train every hour
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min_experiences: 100 # Minimum experiences before training
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training_steps_per_cycle: 10 # Training steps per cycle
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# RL specific training
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rl_training_interval: 300 # Train RL every 5 minutes (was 1 hour)
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min_experiences: 50 # Reduced from 100 for faster learning
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training_steps_per_cycle: 20 # Increased from 10 for more learning
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model_type: "optimized_short_term"
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use_realtime: true
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use_ticks: true
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checkpoint_dir: "NN/models/saved/realtime_ticks_checkpoints"
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save_best_model: true
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save_final_model: false # We only want to keep the best performing model
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# Continuous learning settings
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continuous_learning: true
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learning_from_trades: true
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pattern_recognition: true
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retrospective_learning: true
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# Trading Execution
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trading:
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@ -135,8 +148,8 @@ web:
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host: "127.0.0.1"
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port: 8050
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debug: false
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update_interval: 1000 # Milliseconds
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chart_history: 100 # Number of candles to show
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update_interval: 500 # Milliseconds
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chart_history: 200 # Number of candles to show
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# Enhanced dashboard features
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show_timeframe_analysis: true
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@ -188,4 +201,9 @@ backtesting:
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end_date: "2024-12-31"
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initial_balance: 10000
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commission: 0.0002
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slippage: 0.0001
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slippage: 0.0001
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model_paths:
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realtime_model: "NN/models/saved/optimized_short_term_model_realtime_best.pt"
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ticks_model: "NN/models/saved/optimized_short_term_model_ticks_best.pt"
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backup_model: "NN/models/saved/realtime_ticks_checkpoints/checkpoint_epoch_50449_backup/model.pt"
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