low lr improves rmsprop
@@ -74,24 +74,24 @@ def evaluate(model):
assert accuracy > 0.95
class TestMNIST(unittest.TestCase):
- def test_mnist_conv(self):
+ def conv(self):
np.random.seed(1337)
model = TinyConvNet()
optimizer = optim.Adam([model.c1, model.l1, model.l2], lr=0.001)
train(model, optimizer, steps=400)
evaluate(model)
- def test_mnist_sgd(self):
+ def sgd(self):
np.random.seed(1337)
model = TinyBobNet()
optimizer = optim.SGD([model.l1, model.l2], lr=0.001)
train(model, optimizer, steps=1000)
evaluate(model)
- def test_mnist_rmsprop(self):
+ def rmsprop(self):
np.random.seed(1337)
model = TinyBobNet()
- optimizer = optim.RMSprop([model.l1, model.l2], lr=0.001)
+ optimizer = optim.RMSprop([model.l1, model.l2], lr=0.0002)
train(model, optimizer, steps=1000)
evaluate(model)
