TensorFlow2学习十一之绘制准确率acc和损失函数loss曲线 | 您所在的位置:网站首页 › 神经网络训练准确率曲线 › TensorFlow2学习十一之绘制准确率acc和损失函数loss曲线 |
model.fit中将训练集loss、测试集loss、训练集准确率保存了下来 history=model.fit(训练集数据, 训练集标签, batch_size=, epochs=, validation_split=用作测试数据的比例, validation_data=测试集, validation_freq=测试频率)history包含以下几个属性: 训练集loss: loss 测试集loss: val_loss 训练集准确率: sparse_categorical_accuracy 测试集准确率: val_sparse_categorical_accuracy acc = history.history['sparse_categorical_accuracy'] val_acc = history.history['val_sparse_categorical_accuracy'] loss = history.history['loss'] val_loss = history.history['val_loss']绘制acc和loss曲线: plt.subplot(1, 2, 1) plt.plot(acc, label='Training Accuracy') plt.plot(val_acc, label='Validation Accuracy') plt.title('Training and Validation Accuracy') plt.legend() plt.subplot(1, 2, 2) plt.plot(loss, label='Training Loss') plt.plot(val_loss, label='Validation Loss') plt.title('Training and Validation Loss') plt.legend() plt.show() |
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