Validation loss is less than training loss by 5 units. How this result is interpreted?
The key here is dropout. When a model trains with dropout, only a percentage of the total weights (in your case 50%) are used in predictions, which tends to lower the prediction accuracy. When the validation data is tested, dropout is turned off, and the validation loss tends to be a lot lower. see this answer to a similar question for more info.