From bf9349b9cf8de07e0fd05959d16d083a84055854 Mon Sep 17 00:00:00 2001
From: Jingchao Zhang <6353250+JingchaoZhang@users.noreply.github.com>
Date: Mon, 25 Oct 2021 10:49:04 -0400
Subject: [PATCH] Update training.md

---
 doc/train/training.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/doc/train/training.md b/doc/train/training.md
index b9c6bd4cb8..fd2c175651 100644
--- a/doc/train/training.md
+++ b/doc/train/training.md
@@ -38,7 +38,7 @@ During the training, the error of the model is tested every `disp_freq` training
     400      1.36e+01    1.32e+01      1.07e-02    2.07e-03      4.29e-01    4.19e-01    1.0e-03
     500      1.07e+01    1.05e+01      2.45e-03    4.11e-03      3.38e-01    3.31e-01    1.0e-03
 ```
-The file contains 8 columns, form right to left, are the training step, the validation loss, training loss, root mean square (RMS) validation error of energy, RMS training error of energy, RMS validation error of force, RMS training error of force and the learning rate. The RMS error (RMSE) of the energy is normalized by number of atoms in the system. One can visualize this file by a simple Python script:
+The file contains 8 columns, form left to right, are the training step, the validation loss, training loss, root mean square (RMS) validation error of energy, RMS training error of energy, RMS validation error of force, RMS training error of force and the learning rate. The RMS error (RMSE) of the energy is normalized by number of atoms in the system. One can visualize this file by a simple Python script:
 
 ```py
 import numpy as np
@@ -59,4 +59,4 @@ plt.show()
 Checkpoints will be written to files with prefix `save_ckpt` every `save_freq` training steps. 
 
 ## Warning
-It is warned that the example water data (in folder `examples/water/data`) is of very limited amount, is provided only for testing purpose, and should not be used to train a productive model.
\ No newline at end of file
+It is warned that the example water data (in folder `examples/water/data`) is of very limited amount, is provided only for testing purpose, and should not be used to train a productive model.