1 1 history = model.fit()
2 2
3 3 def plot_acc_loss_curve(history):
4 4 # 显示训练集和验证集的acc和loss曲线
5 5 from matplotlib import pyplot as plt
6 6 acc = history.history['sparse_categorical_accuracy']
7 7 val_acc = history.history['val_sparse_categorical_accuracy']
8 8 loss = history.history['loss']
9 9 val_loss = history.history['val_loss']
10 10
11 11 plt.figure(figsize=(15, 5))
12 12 plt.subplot(1, 2, 1)
13 13 plt.plot(acc, label='Training Accuracy')
14 14 plt.plot(val_acc, label='Validation Accuracy')
15 15 plt.title('Training and Validation Accuracy')
16 16 plt.legend()
17 17 #plt.grid()
18 18
19 19 plt.subplot(1, 2, 2)
20 20 plt.plot(loss, label='Training Loss')
21 21 plt.plot(val_loss, label='Validation Loss')
22 22 plt.title('Training and Validation Loss')
23 23 plt.legend()
24 24 #plt.grid()
25 25 plt.show()
26 26
27 27plot_acc_loss_curve(history)
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