diff --git a/DeepPurpose/dataset.py b/DeepPurpose/dataset.py
index 08f0db4..17b6e7f 100644
--- a/DeepPurpose/dataset.py
+++ b/DeepPurpose/dataset.py
@@ -170,7 +170,7 @@ def download_BindingDB(path = './data'):
 	if not os.path.exists(path):
 	    os.makedirs(path)
 
-	url = 'https://www.bindingdb.org/bind/downloads/BindingDB_All_2020m2.tsv.zip'
+	url = 'https://www.bindingdb.org/bind/downloads/BindingDB_All_2020m11.tsv.zip'
 	saved_path = wget.download(url, path)
 
 	print('Beginning to extract zip file...')
diff --git a/Tutorial_1_DTI_Prediction.ipynb b/Tutorial_1_DTI_Prediction.ipynb
index 1caa372..dbb05c3 100644
--- a/Tutorial_1_DTI_Prediction.ipynb
+++ b/Tutorial_1_DTI_Prediction.ipynb
@@ -263,7 +263,7 @@
    "source": [
     "(**Model configuration generation**) Now, we initialize a model with its configuration. You can modify almost any hyper-parameters (e.g., learning rate, epoch, batch size), model parameters (e.g. hidden dimensions, filter size) and etc in this function. The supported configurations are listed here in this [link](https://github.com/kexinhuang12345/DeepPurpose/blob/e169e2f550694145077bb2af95a4031abe400a77/DeepPurpose/utils.py#L486).\n",
     "\n",
-    "For the sake of example, we specify the epoch size to be 3, and set the model parameters to be small so that you can run on both CPUs & GPUs quickly and can proceed to the next steps. For a reference parameters, checkout the notebooks in the DEMO folder."
+    "For the sake of example, we specify the epoch size to be 5, and set the model parameters to be small so that you can run on both CPUs & GPUs quickly and can proceed to the next steps. For a reference parameters, checkout the notebooks in the DEMO folder."
    ]
   },
   {