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i think we fixed mexc interface at the end!!!

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Dobromir Popov
2025-07-04 02:14:29 +03:00
parent 978cecf0c5
commit cf91e090c8
7 changed files with 445 additions and 613 deletions
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core/orchestrator.py
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@ -1549,38 +1549,28 @@ class TradingOrchestrator:
self.model_states['extrema_trainer']['current_loss'] = estimated_loss
self.model_states['extrema_trainer']['best_loss'] = estimated_loss
# Ensure initial_loss is set for new models
# NO LONGER SETTING SYNTHETIC INITIAL LOSS VALUES
# Keep all None values as None if no real data is available
# This prevents the "fake progress" issue where Current Loss = Initial Loss
# Only set initial_loss from actual training history if available
for model_key, model_state in self.model_states.items():
if model_state['initial_loss'] is None:
# Set reasonable initial loss values for new models
initial_losses = {
'dqn': 0.285,
'cnn': 0.412,
'cob_rl': 0.356,
'decision': 0.298,
'extrema_trainer': 0.356
}
model_state['initial_loss'] = initial_losses.get(model_key, 0.3)
# If current_loss is None, set it to initial_loss
if model_state['current_loss'] is None:
model_state['current_loss'] = model_state['initial_loss']
# If best_loss is None, set it to current_loss
if model_state['best_loss'] is None:
model_state['best_loss'] = model_state['current_loss']
# Leave initial_loss as None if no real training history exists
# Leave current_loss as None if model isn't actively training
# Leave best_loss as None if no checkpoints exist with real performance data
pass # No synthetic data generation
return self.model_states
except Exception as e:
logger.error(f"Error getting model states: {e}")
# Return safe fallback values
# Return None values instead of synthetic data
return {
'dqn': {'initial_loss': 0.285, 'current_loss': 0.285, 'best_loss': 0.285, 'checkpoint_loaded': False},
'cnn': {'initial_loss': 0.412, 'current_loss': 0.412, 'best_loss': 0.412, 'checkpoint_loaded': False},
'cob_rl': {'initial_loss': 0.356, 'current_loss': 0.356, 'best_loss': 0.356, 'checkpoint_loaded': False},
'decision': {'initial_loss': 0.298, 'current_loss': 0.298, 'best_loss': 0.298, 'checkpoint_loaded': False},
'extrema_trainer': {'initial_loss': 0.356, 'current_loss': 0.356, 'best_loss': 0.356, 'checkpoint_loaded': False}
'dqn': {'initial_loss': None, 'current_loss': None, 'best_loss': None, 'checkpoint_loaded': False},
'cnn': {'initial_loss': None, 'current_loss': None, 'best_loss': None, 'checkpoint_loaded': False},
'cob_rl': {'initial_loss': None, 'current_loss': None, 'best_loss': None, 'checkpoint_loaded': False},
'decision': {'initial_loss': None, 'current_loss': None, 'best_loss': None, 'checkpoint_loaded': False},
'extrema_trainer': {'initial_loss': None, 'current_loss': None, 'best_loss': None, 'checkpoint_loaded': False}
}
def update_model_loss(self, model_name: str, current_loss: float, best_loss: float = None):