diff --git a/run.py b/run.py
index bfe1c7ed62d9b2e8a707c117e252ff3f931f339a..5c2e383346084bf5f27e6d425e513984d28a4129 100644
--- a/run.py
+++ b/run.py
@@ -3,6 +3,7 @@ __date__ = '2019-11-14'
 
 
 import argparse
+import json
 
 from src.run_modules.experiment_setup import ExperimentSetup
 from src.run_modules.partition_check import PartitionCheck
@@ -14,11 +15,21 @@ from src.run_modules.training import Training
 
 
 def main(parser_args):
+    
+    station_filename= "German_background_stations.json"  # "German_stations.json"
+    with open(station_filename) as jfile:
+        stations = json.load(jfile)
 
     with RunEnvironment():
-        ExperimentSetup(parser_args, stations=['DEBW107', 'DEBY081', 'DEBW013', 'DEBW076', 'DEBW087', 'DEBW001'],
-                        station_type='background', trainable=False, create_new_model=True, window_history_size=6,
-                        create_new_bootstraps=False)
+
+        ExperimentSetup(parser_args,
+                        #stations=stations,
+                        stations=['DEBW107', 'DEBY081', 'DEBW013', 'DEBW076', 'DEBW087', 'DEBW001'],
+                        station_type='background', window_lead_time=4, window_history_size=6,
+                        trainable=False, create_new_model=True, permute_data_on_training=True,
+                        extreme_values=3., train_min_length=365*5, val_min_length=365, test_min_length=365*2,
+                        create_new_bootstraps=True,)
+
         PreProcessing()
 
         PartitionCheck()
diff --git a/src/model_modules/model_class.py b/src/model_modules/model_class.py
index b46213e591798861fea4f0da13c9bab824200b4b..865cab8842536d2ead53c42f959c51df6f2635be 100644
--- a/src/model_modules/model_class.py
+++ b/src/model_modules/model_class.py
@@ -502,9 +502,10 @@ class MyPaperModel(AbstractModelClass):
         self.channels = channels
         self.dropout_rate = .3
         self.regularizer = keras.regularizers.l2(0.001)
-        self.initial_lr = 1e-3
+        # self.initial_lr = 1e-4
+        self.initial_lr = 0.01
         self.lr_decay = src.model_modules.keras_extensions.LearningRateDecay(base_lr=self.initial_lr, drop=.94, epochs_drop=10)
-        self.epochs = 150
+        self.epochs = 3 # 350
         self.batch_size = int(256 * 2)
         self.activation = keras.layers.ELU
         self.padding = "SymPad2D"
@@ -541,15 +542,15 @@ class MyPaperModel(AbstractModelClass):
         pool_settings_dict1 = {'pool_kernel': (3, 1), 'tower_filter': 16, 'activation': activation}
 
         conv_settings_dict2 = {
-            'tower_1': {'reduction_filter': 64, 'tower_filter': 32 * 2, 'tower_kernel': (3, 1),
+            'tower_1': {'reduction_filter': 64, 'tower_filter': 32 * 2 * 2, 'tower_kernel': (3, 1),
                         'activation': activation},
-            'tower_2': {'reduction_filter': 64, 'tower_filter': 32 * 2, 'tower_kernel': (5, 1),
+            'tower_2': {'reduction_filter': 64, 'tower_filter': 32 * 2 * 2, 'tower_kernel': (5, 1),
                         'activation': activation},
-            'tower_3': {'reduction_filter': 64, 'tower_filter': 32 * 2, 'tower_kernel': (1, 1),
+            'tower_3': {'reduction_filter': 64, 'tower_filter': 32 * 2 * 2, 'tower_kernel': (1, 1),
                         'activation': activation},
             # 'tower_4':{'reduction_filter':8*2, 'tower_filter':16*2, 'tower_kernel':(7,1), 'activation':activation},
         }
-        pool_settings_dict2 = {'pool_kernel': (3, 1), 'tower_filter': 32, 'activation': activation}
+        pool_settings_dict2 = {'pool_kernel': (3, 1), 'tower_filter': 32 * 2, 'activation': activation}
 
         conv_settings_dict3 = {
             'tower_1': {'reduction_filter': 64 * 2, 'tower_filter': 32 * 4, 'tower_kernel': (3, 1),
@@ -571,7 +572,7 @@ class MyPaperModel(AbstractModelClass):
         pad_size = PadUtils.get_padding_for_same(first_kernel)
         # X_in = adv_pad.SymmetricPadding2D(padding=pad_size)(X_input)
         # X_in = inception_model.padding_layer("SymPad2D")(padding=pad_size, name="SymPad")(X_input)  # adv_pad.SymmetricPadding2D(padding=pad_size)(X_input)
-        X_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad")(X_input)
+        X_in = Padding2D(self.padding)(padding=pad_size, name=f"First_{self.padding}")(X_input)
         X_in = keras.layers.Conv2D(filters=first_filters,
                                    kernel_size=first_kernel,
                                    kernel_regularizer=self.regularizer,
@@ -614,3 +615,5 @@ class MyPaperModel(AbstractModelClass):
         self.optimizer = keras.optimizers.SGD(lr=self.initial_lr, momentum=0.9)
         self.compile_options = {"loss": [keras.losses.mean_squared_error, keras.losses.mean_squared_error],
                                 "metrics": ['mse', 'mea']}
+
+
diff --git a/src/run_modules/model_setup.py b/src/run_modules/model_setup.py
index e8259b2847ea4ede1b365f49778f019c004fa7f1..cddebd84d64266a00b1682ebc08032b072420f1a 100644
--- a/src/run_modules/model_setup.py
+++ b/src/run_modules/model_setup.py
@@ -10,9 +10,9 @@ import tensorflow as tf
 
 from src.model_modules.keras_extensions import HistoryAdvanced, CallbackHandler
 # from src.model_modules.model_class import MyBranchedModel as MyModel
-from src.model_modules.model_class import MyLittleModel as MyModel
+# from src.model_modules.model_class import MyLittleModel as MyModel
 # from src.model_modules.model_class import MyTowerModel as MyModel
-# from src.model_modules.model_class import MyPaperModel as MyModel
+from src.model_modules.model_class import MyPaperModel as MyModel
 from src.run_modules.run_environment import RunEnvironment