diff --git a/data/TopTagging/val.h5 b/data/TopTagging/val.h5
new file mode 100644
index 0000000..b7d9ff7
Binary files /dev/null and b/data/TopTagging/val.h5 differ
diff --git a/load_data.py b/load_data.py
index 288dc72..55ca1f3 100644
--- a/load_data.py
+++ b/load_data.py
@@ -12,19 +12,19 @@ def read_files(DATAPATH, dataset, verbose=True):
 		if dataset in file:
 			if verbose:
 				print("Reading data from {}".format(file))
-				events = pd.read_hdf(os.path.join(DATAPATH, file), key='table').values
+				events = pd.read_hdf(os.path.join(DATAPATH, file), key='data').values
 
 	return events
 
 def Loader(dataset, batch_size, test):
 
-	datapath = './data/top_tagging'
+	datapath = './data/TopTagging'
 	data = read_files(datapath, dataset)	
 
 	if test == True:
 		split = int(len(data) * 0.01)
 	else:	
-		split = int(len(data) * 0.01)
+		split = int(len(data) * 1.0)
 
 	events=data
 	events_train = events[:split]
diff --git a/train.py b/train.py
index 00e294d..b1da5e9 100644
--- a/train.py
+++ b/train.py
@@ -20,8 +20,8 @@
 print(model)
 print('Total parameters: %d' % sum([np.prod(p.size()) for p in model.params_trainable]))
 
-train_loader, train_size, data_shape = Loader('train_img40_add', c.batch_size, False)
-val_loader, val_size, data_shape   = Loader('test_img40_add', c.batch_size, False)
+train_loader, train_size, data_shape = Loader('train', c.batch_size, False)
+val_loader, val_size, data_shape     = Loader('val', c.batch_size, False)
 
 N_epochs = c.n_epochs
 t_start = time()