diff --git a/src/twomartens/masterthesis/aae/run.py b/src/twomartens/masterthesis/aae/run.py
index 4ad3164..f78d59e 100644
--- a/src/twomartens/masterthesis/aae/run.py
+++ b/src/twomartens/masterthesis/aae/run.py
@@ -39,9 +39,9 @@ tfe = tf.contrib.eager
 def run_simple(dataset: tf.data.Dataset,
                iteration: int,
                weights_prefix: str,
-               channels: int = 1,
-               zsize: int = 32,
-               batch_size: int = 128,
+               channels: int = 3,
+               zsize: int = 64,
+               batch_size: int = 16,
                verbose: bool = False,
                debug: bool = False) -> None:
     """
@@ -53,9 +53,9 @@ def run_simple(dataset: tf.data.Dataset,
         dataset: run dataset
         iteration: identifier for the used training run
         weights_prefix: prefix for trained weights directory
-        channels: number of channels in input image (default: 1)
-        zsize: size of the intermediary z (default: 32)
-        batch_size: size of each batch (default: 128)
+        channels: number of channels in input image (default: 3)
+        zsize: size of the intermediary z (default: 64)
+        batch_size: size of each batch (default: 16)
         verbose: if True training progress is printed to console (default: False)
         debug: if True summaries are collected (default: False)
     """
diff --git a/src/twomartens/masterthesis/aae/train.py b/src/twomartens/masterthesis/aae/train.py
index 43e666c..5f9037b 100644
--- a/src/twomartens/masterthesis/aae/train.py
+++ b/src/twomartens/masterthesis/aae/train.py
@@ -47,11 +47,11 @@ LOG_FREQUENCY: int = 10
 def train_simple(dataset: tf.data.Dataset,
                  iteration: int,
                  weights_prefix: str,
-                 channels: int = 1,
-                 zsize: int = 32,
-                 lr: float = 0.002,
-                 train_epoch: int = 80,
-                 batch_size: int = 128,
+                 channels: int = 3,
+                 zsize: int = 64,
+                 lr: float = 0.0001,
+                 train_epoch: int = 1,
+                 batch_size: int = 16,
                  verbose: bool = False,
                  debug: bool = False) -> None:
     """
@@ -68,11 +68,11 @@ def train_simple(dataset: tf.data.Dataset,
         dataset: train dataset
         iteration: identifier for the current training run
         weights_prefix: prefix for weights directory
-        channels: number of channels in input image (default: 1)
-        zsize: size of the intermediary z (default: 32)
-        lr: initial learning rate (default: 0.002)
-        train_epoch: number of epochs to train (default: 80)
-        batch_size: size of each batch (default: 128)
+        channels: number of channels in input image (default: 3)
+        zsize: size of the intermediary z (default: 64)
+        lr: initial learning rate (default: 0.0001)
+        train_epoch: number of epochs to train (default: 1)
+        batch_size: size of each batch (default: 16)
         verbose: if True training progress is printed to console (default: False)
         debug: if True summaries are collected (default: False)
     """