diff --git a/README.md b/README.md
index 2c4c6ad..416e24d 100644
--- a/README.md
+++ b/README.md
@@ -1,27 +1,33 @@
 # MTGNN
+
 This is a PyTorch implementation of the paper: [Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks](https://arxiv.org/abs/2005.11650), published in KDD-2020.
 
 ## Requirements
+
 The model is implemented using Python3 with dependencies specified in requirements.txt
+
 ## Data Preparation
+
 ### Multivariate time series datasets
 
 Download Solar-Energy, Traffic, Electricity, Exchange-rate datasets from [https://github.com/laiguokun/multivariate-time-series-data](https://github.com/laiguokun/multivariate-time-series-data). Uncompress them and move them to the data folder.
 
 ### Traffic datasets
+
 Download the METR-LA and PEMS-BAY dataset from [Google Drive](https://drive.google.com/open?id=10FOTa6HXPqX8Pf5WRoRwcFnW9BrNZEIX) or [Baidu Yun](https://pan.baidu.com/s/14Yy9isAIZYdU__OYEQGa_g) provided by [Li et al.](https://github.com/liyaguang/DCRNN.git) . Move them into the data folder. 
 
 ```
-
 # Create data directories
+
 mkdir -p data/{METR-LA,PEMS-BAY}
 
 # METR-LA
+
 python generate_training_data.py --output_dir=data/METR-LA --traffic_df_filename=data/metr-la.h5
 
 # PEMS-BAY
-python generate_training_data.py --output_dir=data/PEMS-BAY --traffic_df_filename=data/pems-bay.h5
 
+python generate_training_data.py --output_dir=data/PEMS-BAY --traffic_df_filename=data/pems-bay.h5
 ```
 
 ## Model Training
@@ -32,14 +38,15 @@ python generate_training_data.py --output_dir=data/PEMS-BAY --traffic_df_filenam
 
 ```
 python train_single_step.py --save ./model-solar-3.pt --data ./data/solar_AL.txt --num_nodes 137 --batch_size 4 --epochs 30 --horizon 3
-#sampling
+# sampling
 python train_single_step.py --num_split 3 --save ./model-solar-sampling-3.pt --data ./data/solar_AL.txt --num_nodes 137 --batch_size 16 --epochs 30 --horizon 3
 ```
-* Traffic 
+
+* Traffic
 
 ```
 python train_single_step.py --save ./model-traffic3.pt --data ./data/traffic.txt --num_nodes 862 --batch_size 16 --epochs 30 --horizon 3
-#sampling
+# sampling
 python train_single_step.py --num_split 3 --save ./model-traffic-sampling-3.pt --data ./data/traffic --num_nodes 321 --batch_size 16 --epochs 30 --horizon 3
 ```
 
@@ -47,7 +54,7 @@ python train_single_step.py --num_split 3 --save ./model-traffic-sampling-3.pt -
 
 ```
 python train_single_step.py --save ./model-electricity-3.pt --data ./data/electricity.txt --num_nodes 321 --batch_size 4 --epochs 30 --horizon 3
-#sampling 
+# sampling
 python train_single_step.py --num_split 3 --save ./model-electricity-sampling-3.pt --data ./data/electricity.txt --num_nodes 321 --batch_size 16 --epochs 30 --horizon 3
 ```
 
@@ -58,12 +65,15 @@ python train_single_step.py --save ./model/model-exchange-3.pt --data ./data/exc
 #sampling
 python train_single_step.py --num_split 3 --save ./model-exchange-3.pt --data ./data/exchange_rate.txt --num_nodes 8 --subgraph_size 2  --batch_size 16 --epochs 30 --horizon 3
 ```
+
 ### Multi-step
+
 * METR-LA
 
 ```
 python train_multi_step.py --adj_data ./data/sensor_graph/adj_mx.pkl --data ./data/METR-LA --num_nodes 207
 ```
+
 * PEMS-BAY
 
 ```