How should I sample my validation set if I randomly sample training data?
Actually you should never use any sampling techniques on your testing/evaluation data because this could lead to wrong classification results.
If your dataset is imbalanced you could perform upsampling or downsampling techniques (like SMOTE) on your training data only.
If you want to benchmark your multi-class classification you need to rely on e.g. the confusion matrix, recall, precision and F1 measure. Please keep in mind that the accuracy measure cannot be interpreted if you have too imbalanced data.