784 input neurons, 60 neurons, 10 output neurons

gistfile1.txt

import mnist_loader
training_data, validation_data, test_data = mnist_loader.load_data_wrapper()

import network2
net = network2.Network([784, 30, 10], cost=network2.CrossEntropyCost)

net.large_weight_initializer()
net.SGD(training_data, 30, 10, 0.5, evaluation_data=test_data, monitor_evaluation_accuracy=True)

<<<<<<<<<< Snippet Output >>>>>>>>>>>
In [12]: net.SGD(training_data, 30, 10, 0.5, evaluation_data=test_data, monitor_evaluation_accuracy=True)
Epoch 0 training complete
Accuracy on evaluation data: 9135 / 10000

Epoch 1 training complete
Accuracy on evaluation data: 9274 / 10000

Epoch 2 training complete
Accuracy on evaluation data: 9300 / 10000

<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
# network basic
net = Network([784, 60, 10])
net.SGD(training_data, 60, 10, 3.0, test_data=test_data)
Epoch 59: 9597 / 10000

net.SGD(training_data, 60, 10, 2.0, test_data=test_data)
Epoch 59: 9598 / 10000

net.SGD(training_data, 60, 10, 1.0, test_data=test_data)
Epoch 59: 9540 / 10000