Update README.md

README.md

@@ -38,15 +38,14 @@ and run
 python main.py
 ```
 
-Default parameters are not the best performing-hyper-parameters. Hyper-parameters need to be specified through the commandline arguments. Please refer to our paper for the details of how we set the hyper-parameters.
-
-Type
+The default parameters are not the best performing-hyper-parameters used to reproduce our results in the paper. Hyper-parameters need to be specified through the commandline arguments. Please refer to our paper for the details of how we set the hyper-parameters. For instance, for the COLLAB and IMDB datasets, you need to add `--degree_as_tag` so that the node degrees are used for input node features.
 
+To learn hyper-parameters to be specified, please type
 ```
 python main.py --help
 ```
 
-to learn hyper-parameters to be specified.
+
 
 ## Cross-validation strategy in the paper
 The cross-validation in our paper only uses training and validation sets (no test set) due to small dataset size. Specifically, after obtaining 10 validation curves corresponding to 10 folds, we first took average of validation curves across the 10 folds (thus, we obtain an averaged validation curve), and then selected a single epoch that achieved the maximum averaged validation accuracy. Finally, the standard devision over the 10 folds was computed at the selected epoch.