diff --git a/Infer_1Photon.py b/Infer_1Photon.py
index 93a694c..ff5f169 100644
--- a/Infer_1Photon.py
+++ b/Infer_1Photon.py
@@ -1,5 +1,8 @@
 import sys
 sys.path.append('./src')
+import matplotlib
+matplotlib.use('Agg')
+
 from pathlib import Path
 from omegaconf import OmegaConf
 import torch
diff --git a/Infer_2Photon.py b/Infer_2Photon.py
index f2f6c27..00d9418 100644
--- a/Infer_2Photon.py
+++ b/Infer_2Photon.py
@@ -1,5 +1,8 @@
 import sys
 sys.path.append('./src')
+import matplotlib
+matplotlib.use('Agg')
+
 from pathlib import Path
 from omegaconf import OmegaConf
 import torch
diff --git a/Infer_3Photon.py b/Infer_3Photon.py
index 69b9aad..919226f 100644
--- a/Infer_3Photon.py
+++ b/Infer_3Photon.py
@@ -1,5 +1,8 @@
 import sys
 sys.path.append('./src')
+import matplotlib
+matplotlib.use('Agg')
+
 from pathlib import Path
 from omegaconf import OmegaConf
 import torch
diff --git a/Train_1Photon.py b/Train_1Photon.py
index 58e70e9..8b7b7e6 100644
--- a/Train_1Photon.py
+++ b/Train_1Photon.py
@@ -1,5 +1,8 @@
 import sys
 sys.path.append('./src')
+import matplotlib
+matplotlib.use('Agg')
+
 from omegaconf import OmegaConf ### for yaml config parsing
 import torch
 import numpy as np 
@@ -173,6 +176,7 @@ def plot_loss_curve(train_losses, val_losses, test_loss, exp_name, conf):
     if conf.data.normalize:
         plotName += '_normalized'
     plt.savefig(f'Results/{exp_name}/Plots/{plotName}.png')
+    plt.close()
 
 def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, test_rms_y, exp_name, conf):
     import matplotlib.pyplot as plt
@@ -192,6 +196,7 @@ def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, t
     if conf.data.normalize:
         plotName += '_normalized'
     plt.savefig(f'Results/{exp_name}/Plots/{plotName}.png')
+    plt.close()
 
 def get_model_name(epoch, conf):
     modelName = f'singlePhoton{conf.model.version}_{conf.data.energy}keV_Noise{conf.data.noise_keV}keV_E{epoch}_aug{conf.data.num_aug_ops}'
diff --git a/Train_2Photon.py b/Train_2Photon.py
index 50b6c38..fa066fd 100644
--- a/Train_2Photon.py
+++ b/Train_2Photon.py
@@ -1,5 +1,8 @@
 import sys
 sys.path.append('./src')
+import matplotlib
+matplotlib.use('Agg')
+
 from omegaconf import OmegaConf ### for yaml config parsing
 import torch
 from torch import nn
@@ -27,14 +30,14 @@ def prepare_output_folder(conf):
     # find the next index for experiment name
     exp_index = 0
     while True:
-        exp_name = f'{date}_2ph_{conf.data.energy}keV_v{conf.model.version}_{exp_index:02d}'
-        if not Path(f'Results/{exp_name}').exists():
+        exp_name = f'{date}_{conf.data.energy}keV_v{conf.model.version}_{exp_index:02d}'
+        if not Path(f'Results/2ph/{exp_name}').exists():
             break
         exp_index += 1
-    Path(f'Results/{exp_name}').mkdir(parents=True, exist_ok=True)
-    Path(f'Results/{exp_name}/Models').mkdir(parents=True, exist_ok=True)
-    Path(f'Results/{exp_name}/Plots').mkdir(parents=True, exist_ok=True)
-    OmegaConf.save(conf, f'Results/{exp_name}/config.yaml')
+    Path(f'Results/2ph/{exp_name}').mkdir(parents=True, exist_ok=True)
+    Path(f'Results/2ph/{exp_name}/Models').mkdir(parents=True, exist_ok=True)
+    Path(f'Results/2ph/{exp_name}/Plots').mkdir(parents=True, exist_ok=True)
+    OmegaConf.save(conf, f'Results/2ph/{exp_name}/config.yaml')
     return exp_name
 
 def get_loss_function(conf):
@@ -208,7 +211,7 @@ def plot_loss_curves(train_losses, val_losses, test_loss, exp_name, conf):
     plt.legend()
     plt.grid()
     plotName = f'loss_curve_doublePhoton_{conf.model.version}.png'
-    plt.savefig(f'Results/{exp_name}/Plots/{plotName}')
+    plt.savefig(f'Results/2ph/{exp_name}/Plots/{plotName}')
     plt.close()
 
 def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, test_rms_y, exp_name, conf):
@@ -226,7 +229,8 @@ def plot_rms_curve(train_rms_x, train_rms_y, val_rms_x, val_rms_y, test_rms_x, t
     plt.legend()
     plt.grid()
     plotName = f'rms_curve_doublePhoton_{conf.model.version}'
-    plt.savefig(f'Results/{exp_name}/Plots/{plotName}.png')
+    plt.savefig(f'Results/2ph/{exp_name}/Plots/{plotName}.png')
+    plt.close()
     
 def get_model_name(conf):
     modelName = f'doublePhoton{conf.model.version}_{conf.data.energy}keV_Noise{conf.data.noise_keV}keV'
@@ -260,7 +264,7 @@ if __name__ == "__main__":
         print(f"Learning Rate: {optimizer.param_groups[0]['lr']:.2e}")
         if epoch in conf.training.checkpoint_epochs or epoch == conf.training.epochs:
             modelName = get_model_name(conf)
-            torch.save(model.state_dict(), f'Results/{exp_name}/Models/{modelName}_E{epoch}.pth')
+            torch.save(model.state_dict(), f'Results/2ph/{exp_name}/Models/{modelName}_E{epoch}.pth')
             print(f"Saved model checkpoint: {modelName}_E{epoch}.pth")
             plot_loss_curves(TrainLosses, ValLosses, test_loss=-1, exp_name=exp_name, conf=conf)
             plot_rms_curve(train_rms_xs, train_rms_ys, val_rms_xs, val_rms_ys, test_rms_x = -1, test_rms_y = -1, exp_name=exp_name, conf=conf)
diff --git a/Train_3Photon.py b/Train_3Photon.py
index 67c91ef..8979beb 100644
--- a/Train_3Photon.py
+++ b/Train_3Photon.py
@@ -1,5 +1,8 @@
 import sys
 sys.path.append('./src')
+import matplotlib
+matplotlib.use('Agg')
+
 from omegaconf import OmegaConf ### for yaml config parsing
 import torch
 import numpy as np 
@@ -134,6 +137,7 @@ def plot_loss_curves(train_losses, val_losses, test_loss, exp_name, conf):
     plt.grid()
     plotName = f'loss_curve_triplePhoton_{conf.model.version}.png'
     plt.savefig(f'Results/{exp_name}/Plots/{plotName}')
+    plt.close()
 
 def get_model_name(conf):
     modelName = f'triplePhoton{conf.model.version}_{conf.data.energy}keV'