diff --git a/README.rst b/README.rst
index 31f8b31..6827a76 100644
--- a/README.rst
+++ b/README.rst
@@ -37,6 +37,8 @@ Benchmarks
 
 Here are the results of testing 10 epochs of training for two-thirds of the original MNIST data, on Ubuntu 14.04 and a GeForce GTX 650 (Memory: 1024Mb, Cores: 384).  You can run ``examples/bench_mnist.py`` to get the results.
 
+.. class:: center
+
 ==========  ============  ===============  ===================
    MNIST      sknn.mlp      nolearn.dbn      nolearn.lasagne
 ==========  ============  ===============  ===================
diff --git a/sknn/tests/test_training.py b/sknn/tests/test_training.py
index 3c0f452..4ff8bad 100644
--- a/sknn/tests/test_training.py
+++ b/sknn/tests/test_training.py
@@ -34,10 +34,10 @@ def test_VerboseRegressor(self):
         nn = sknn.mlp.MultiLayerPerceptronRegressor(layers=[("Linear",)], verbose=1, n_iter=1)
         a_in, a_out = numpy.zeros((8,16)), numpy.zeros((8,4))
         nn.fit(a_in, a_out)
-        assert_in("Epoch 0, R^2 1.000000", self.buf.getvalue())
+        assert_in("Epoch 0, score = 1.000000", self.buf.getvalue())
 
     def test_VerboseClassifier(self):
         nn = sknn.mlp.MultiLayerPerceptronClassifier(layers=[("Linear",)], verbose=1, n_iter=1)
         a_in, a_out = numpy.zeros((8,16)), numpy.zeros((8,1), dtype=numpy.int32)
         nn.fit(a_in, a_out)
-        assert_in("Epoch 0, R^2 1.000000", self.buf.getvalue())
+        assert_in("Epoch 0, score = 1.000000", self.buf.getvalue())