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fix mem leak and train loss

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Dobromir Popov
2025-11-12 18:17:21 +02:00
parent 4a5c3fc943
commit 4f43d0d466
2 changed files with 76 additions and 97 deletions
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7
NN/models/advanced_transformer_trading.py
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@@ -1307,12 +1307,15 @@ class TradingTransformerTrainer:
candle_losses_detail[tf] = tf_loss.item()
# ALSO calculate denormalized loss for better interpretability
# Use RMSE (Root Mean Square Error) instead of MSE for realistic values
if tf in norm_params:
with torch.no_grad():
pred_denorm = self.denormalize_candle(pred_candle, norm_params[tf])
target_denorm = self.denormalize_candle(target_candle, norm_params[tf])
denorm_loss = self.price_criterion(pred_denorm, target_denorm)
candle_losses_denorm[tf] = denorm_loss.item()
# Use RMSE instead of MSE to get interpretable dollar values
mse = torch.mean((pred_denorm - target_denorm) ** 2)
rmse = torch.sqrt(mse + 1e-8) # Add epsilon for numerical stability
candle_losses_denorm[tf] = rmse.item()
# Average loss across available timeframes
if timeframe_losses: