180304 the Acc+loss+val_acc+val_loss in the training process of keras in the image viewing model

- First Step

# define the function
def training_vis (hist):
    loss = hist.history[' loss ']
    Val_loss = hist.history[' Val_ Loss ']
    acc = hist.history[' acc ']
    VAL_ACC = hist.history[' Val_acc ']

    # make a figure
    fig = plt.figure ( Figsize= (8,4))
    # subplot loss
    Ax1 = fig.add_subplot (121)
    Ax1.plot (loss,label= ' Train_loss ')
    Ax1.plot (val_loss,label= ' Val_loss ')
    ax1.set_xlabel (' epochs ')
    Ax1.set_ylabel (' loss ')
    ax1.set_ Title (' Loss on Training and Validation Data ')
    ax1.legend ()
    # subplot acc
    ax2 = fig.add_subplot (122)
    ax2.plot (acc,label= ' TRAIN_ACC ')
    ax2.plot (val_acc,label= ' VAL_ACC ')
    ax2.set_xlabel (' epochs ')
    Ax2.set_ylabel (' accuracy ')
    ax2.set_title (' accuracy on  Training and Validation Data ')
    Ax2.legend ()
    plt.tight_layout ()

Step Two

# Train the model
hist = Model.fit (...)

Step three

# Call the function
Training_vis (hist)