如何使用 Tensorflow 来使用 Python 训练模型?
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可以使用 Tensorflow 中的‘train’方法训练模型，其中指定了 epoch(数据必须训练才能适合模型的次数)和训练数据。
阅读更多: 什么是 TensorFlow，以及 Keras 如何与 TensorFlow 配合使用来创建神经网络?
我们正在使用 Google Colaboratory 来运行以下代码。 Google Colab 或 Colaboratory 可帮助在浏览器上运行 Python 代码，无需配置，可免费访问 GPU(图形处理单元)。Colaboratory 建立在 Jupyter Notebook 之上。
print("The model is being training")
epochs=12
history = model.fit(
train_ds,
validation_data=val_ds,
epochs=epochs
)
代码来源:https://www.tensorflow.org/tutorials/images/classification
输出
The model is being training Epoch 1/12 92/92 [==============================] - 94s 1s/step - loss: 1.6007 - accuracy: 0.3411 - val_loss: 1.0708 - val_accuracy: 0.5627 Epoch 2/12 92/92 [==============================] - 92s 995ms/step - loss: 1.0138 - accuracy: 0.5843 - val_loss: 0.9451 - val_accuracy: 0.6458 Epoch 3/12 92/92 [==============================] - 91s 990ms/step - loss: 0.8382 - accuracy: 0.6767 - val_loss: 0.9054 - val_accuracy: 0.6471 Epoch 4/12 92/92 [==============================] - 90s 984ms/step - loss: 0.6362 - accuracy: 0.7580 - val_loss: 0.8872 - val_accuracy: 0.6540 Epoch 5/12 92/92 [==============================] - 94s 1s/step - loss: 0.4125 - accuracy: 0.8572 - val_loss: 0.9114 - val_accuracy: 0.6676 Epoch 6/12 92/92 [==============================] - 91s 988ms/step - loss: 0.2460 - accuracy: 0.9207 - val_loss: 1.0891 - val_accuracy: 0.6757 Epoch 7/12 92/92 [==============================] - 91s 988ms/step - loss: 0.1721 - accuracy: 0.9532 - val_loss: 1.2619 - val_accuracy: 0.6635 Epoch 8/12 92/92 [==============================] - 90s 983ms/step - loss: 0.0658 - accuracy: 0.9823 - val_loss: 1.4119 - val_accuracy: 0.6703 Epoch 9/12 92/92 [==============================] - 90s 983ms/step - loss: 0.0556 - accuracy: 0.9865 - val_loss: 1.6113 - val_accuracy: 0.6090 Epoch 10/12 92/92 [==============================] - 91s 992ms/step - loss: 0.0805 - accuracy: 0.9729 - val_loss: 1.9744 - val_accuracy: 0.6390 Epoch 11/12 92/92 [==============================] - 90s 979ms/step - loss: 0.0545 - accuracy: 0.9838 - val_loss: 1.9303 - val_accuracy: 0.6662 Epoch 12/12 92/92 [==============================] - 96s 1s/step - loss: 0.0176 - accuracy: 0.9961 - val_loss: 1.8234 - val_accuracy: 0.6540
解释
- 模型经过训练以适合数据。
- 这是使用"fit"方法完成的。
