diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 8a66e552ef97fafa4d23817fcb7bde6b02848554..f98a14fa48e6e0ae653b64ac0569bbeddce6446a 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -23,7 +23,7 @@ else:
     NumLogits = NumClasses
 
 BATCH_SIZE = 128
-NUM_EPOCHS = 60
+NUM_EPOCHS = 80
 
 TRACK_MOVING_AVERAGE = False
 EARLY_STOP = True
@@ -32,6 +32,8 @@ NOISE_TRAINING = False
 NOISE_STDDEV = 0.10
 DO_AUGMENT = True
 
+DO_ZERO_OUT = False
+
 # setup scaling parameters dictionary
 mean_std_dct = {}
 mean_std_file = ancillary_path+'mean_std_lo_hi_l2.pkl'
@@ -47,17 +49,13 @@ f.close()
 mean_std_dct.update(mean_std_dct_l1b)
 mean_std_dct.update(mean_std_dct_l2)
 
-# params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'refl_0_65um_nom', 'cloud_fraction']
-# data_params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'refl_0_65um_nom']
 params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'refl_0_65um_nom', 'cloud_fraction']
 data_params = ['temp_11_0um_nom']
 label_params = ['cloud_fraction']
 
+label_param = 'cloud_fraction'
+label_idx = params.index(label_param)
 
-DO_ZERO_OUT = False
-
-label_idx = 3
-label_param = params[label_idx]
 print('data_params: ', data_params)
 print('label_params: ', label_params)