标签:tor poc kaggle amp keras ati com pre get
深度学习严重依赖训练数据量的大小,前面(https://www.cnblogs.com/zhengbiqing/p/11070783.html)只随机抽取猫狗图片各1000、500、200分别作为训练、验证、测试集,即使采用了数据增强,精度只达到83%。
采用kaggle 猫狗数据集全部25000张进行训练学习,随机选取猫狗图片各9000、2250、1250分别作为训练、验证、测试集,进行训练。
训练100次迭代:
history = model.fit_generator( train_generator, steps_per_epoch=train_generator.samples // batch_size, epochs=100, validation_data=validation_generator, validation_steps=validation_generator.samples // batch_size)
Epoch 1/100 281/281 [==============================] - 140s 498ms/step - loss: 0.6736 - acc: 0.5683 - val_loss: 0.6532 - val_acc: 0.6074 Epoch 2/100 281/281 [==============================] - 74s 262ms/step - loss: 0.6358 - acc: 0.6310 - val_loss: 0.5861 - val_acc: 0.6803 Epoch 3/100 281/281 [==============================] - 73s 261ms/step - loss: 0.6094 - acc: 0.6625 - val_loss: 0.5559 - val_acc: 0.7146 Epoch 4/100 281/281 [==============================] - 73s 261ms/step - loss: 0.5936 - acc: 0.6807 - val_loss: 0.5511 - val_acc: 0.7216 Epoch 5/100 281/281 [==============================] - 73s 260ms/step - loss: 0.5797 - acc: 0.6918 - val_loss: 0.5308 - val_acc: 0.7347 Epoch 6/100 281/281 [==============================] - 73s 261ms/step - loss: 0.5681 - acc: 0.7018 - val_loss: 0.5318 - val_acc: 0.7356
......
Epoch 96/100 281/281 [==============================] - 74s 264ms/step - loss: 0.2963 - acc: 0.8717 - val_loss: 0.3118 - val_acc: 0.8614 Epoch 97/100 281/281 [==============================] - 74s 263ms/step - loss: 0.2983 - acc: 0.8726 - val_loss: 0.2581 - val_acc: 0.8862 Epoch 98/100 281/281 [==============================] - 74s 263ms/step - loss: 0.2936 - acc: 0.8781 - val_loss: 0.2546 - val_acc: 0.8922 Epoch 99/100 281/281 [==============================] - 74s 263ms/step - loss: 0.3047 - acc: 0.8711 - val_loss: 0.2548 - val_acc: 0.8884 Epoch 100/100 281/281 [==============================] - 74s 263ms/step - loss: 0.3013 - acc: 0.8744 - val_loss: 0.2745 - val_acc: 0.8848
训练曲线:
用测试集对模型进行测试:
test_generator = test_datagen.flow_from_directory( test_dir, target_size=(150, 150), batch_size=batch_size, class_mode=‘binary‘) test_loss, test_acc = model.evaluate_generator(test_generator, steps=test_generator.samples // batch_size) print(‘test acc:‘, test_acc)
Found 2500 images belonging to 2 classes. test acc: 0.9
混淆矩阵:
标签:tor poc kaggle amp keras ati com pre get
原文地址:https://www.cnblogs.com/zhengbiqing/p/11768706.html