diff --git a/pysegcnn/core/trainer.py b/pysegcnn/core/trainer.py
index 39e677d1849f232d1e8fe6328d4c296189f372a6..88e0fc624c0999dd9a9ed2802a9e9f6dafa4b09d 100644
--- a/pysegcnn/core/trainer.py
+++ b/pysegcnn/core/trainer.py
@@ -2738,7 +2738,6 @@ class NetworkInference(BaseConfig):
             # compute k-fold average estimate of each metric across all models
             LOGGER.info('Calculating k-fold estimate of metrics ...')
             report = df.groupby(df.index, sort=False).mean()
-            inference['report'] = report
 
             # labels to predict
             labels = list(report.index.drop(['macro avg', 'weighted avg',
@@ -2749,7 +2748,7 @@ class NetworkInference(BaseConfig):
             report_name = self.report_path.joinpath(self.report_name(kfold))
             fig.savefig(report_name, dpi=300, bbox_inches='tight')
 
-            # chech whether to compute the aggregated confusion matrix
+            # check whether to compute the aggregated confusion matrix
             if self.cm:
                 # initialize the aggregated confusion matrix
                 cm_agg = np.zeros(shape=2 * (len(labels), ))
@@ -2765,4 +2764,7 @@ class NetworkInference(BaseConfig):
                 plot_confusion_matrix(cm_agg, labels, state_file=kfold,
                                       outpath=self.perfmc_path)
 
+            # add aggregated classification report
+            inference['report'] = report
+
         return inference