diff --git a/dfencoder/autoencoder.py b/dfencoder/autoencoder.py
index 191723c..9f951d8 100644
--- a/dfencoder/autoencoder.py
+++ b/dfencoder/autoencoder.py
@@ -164,7 +164,8 @@ def __init__(self,
                  run=None,
                  progress_bar=True,
                  n_megabatches=1,
-                 scaler='standard', # scaler for the numerical features
+                 scaler='standard',
+                 patience=5,
                  preset_cats=None,
                  loss_scaler='standard',  # scaler for the losses (z score)
                  *args,
@@ -225,8 +226,9 @@ def __init__(self,
         self.logdir = logdir
         self.run = run
         self.project_embeddings = project_embeddings
-
         self.scaler = scaler
+        self.patience = patience
+
         # scaler class used to scale losses and collect loss stats
         self.loss_scaler_str = loss_scaler
         self.loss_scaler = self.get_scaler(loss_scaler)
@@ -688,6 +690,9 @@ def fit(
         n_updates = len(df) // self.batch_size
         if len(df) % self.batch_size > 0:
             n_updates += 1
+        last_loss = 5000
+        
+        count_es = 0
         for i in range(epochs):
             self.train()
             if self.verbose:
@@ -726,6 +731,28 @@ def fit(
                         _, _, _, net_loss = self.compute_loss(num, bin, cat, slc_out, _id=True)
                         id_loss.append(net_loss)
 
+                    # Early stopping
+                    current_net_loss = net_loss
+                    if self.verbose:
+                        print('The Current Net Loss:', current_net_loss)
+
+                    if current_net_loss > last_loss:
+                        count_es += 1
+                        if self.verbose:
+                            print('Early stop count:', count_es)
+
+                        if count_es >= self.patience:
+                            if self.verbose:
+                                print('Early stopping: early stop count({}) >= patience({})'.format(count_es, self.patience))
+                            break
+
+                    else:
+                        if self.verbose:
+                            print('Set count for earlystop: 0')
+                        count_es = 0
+
+                    last_loss = current_net_loss
+
                     self.logger.end_epoch()
                     #                     if self.project_embeddings:
                     #                         self.logger.show_embeddings(self.categorical_fts)