minor edit

ktrain/core.py

@@ -663,15 +663,14 @@ def lr_estimate(self):
         """
         ```
         Return numerical estimates of lr using two different methods:
-            1. learning rate associated with minimum numerical gradient
-            2. learning rate associated with minimum loss divided by 10
-        Since neither of these methods are fool-proof and can
+          1. lr associated with minum numerical gradient (None if gradient computation fails)
+          2. lr associated with minimum loss divided by 10
+          3. lr associated with longest valley
+        Since none of these methods are fool-proof and can
         potentially return bad estimates, it is recommended that you
         examine the plot generated by lr_plot to estimate the learning rate.
         Returns:
-          tuple: tuple of the form (float, float), where
-            First element is lr associated with minimum numerical gradient (None if gradient computation fails).
-            Second element is lr associated with minimum loss divided by 10.
+          tuple: tuple of the form (float, float)
         ```
         """
         if self.lr_finder is None or not self.lr_finder.find_called():