diff --git a/doc/train/training.md b/doc/train/training.md
index b9c6bd4cb8..939afb7df0 100644
--- a/doc/train/training.md
+++ b/doc/train/training.md
@@ -26,7 +26,7 @@ DEEPMD INFO                                        system  natoms  bch_sz   n_bc
 DEEPMD INFO                          ../data_water/data_3     192       1      80  1.000    T
 DEEPMD INFO    --------------------------------------------------------------------------------------
 ```
-The DeePMD-kit prints detailed informaiton on the training and validation data sets. The data sets are defined by `"training_data"` and `"validation_data"` defined in the `"training"` section of the input script. The training data set is composed by three data systems, while the validation data set is composed by one data system. The number of atoms, batch size, number of batches in the system and the probability of using the system are all shown on the screen. The last column presents if the periodic boundary condition is assumed for the system. 
+The DeePMD-kit prints detailed information on the training and validation data sets. The data sets are defined by `"training_data"` and `"validation_data"` defined in the `"training"` section of the input script. The training data set is composed by three data systems, while the validation data set is composed by one data system. The number of atoms, batch size, number of batches in the system and the probability of using the system are all shown on the screen. The last column presents if the periodic boundary condition is assumed for the system. 
 
 During the training, the error of the model is tested every `disp_freq` training steps with the batch used to train the model and with `numb_btch` batches from the validating data. The training error and validation error are printed correspondingly in the file `disp_file` (default is `lcurve.out`). The batch size can be set in the input script by the key `batch_size` in the corresponding sections for training and validation data set. An example of the output 
 ```bash
@@ -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.