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diff --git a/tensorflow/g3doc/tutorials/image_recognition/index.md b/tensorflow/g3doc/tutorials/image_recognition/index.md index 1d20d7ddb3..d4fa5ba780 100644 --- a/tensorflow/g3doc/tutorials/image_recognition/index.md +++ b/tensorflow/g3doc/tutorials/image_recognition/index.md @@ -42,8 +42,8 @@ For example, here are the results from [AlexNet] classifying some images: To compare models, we examine how often the model fails to predict the correct answer as one of their top 5 guesses -- termed "top-5 error rate". [AlexNet] achieved by setting a top-5 error rate of 15.3% on the 2012 -validation data set; [BN-Inception-v2] achieved 6.66%; -[Inception-v3] reaches 3.46%. +validation data set; [Inception (GoogLeNet)] achieved 6.67%; +[BN-Inception-v2] achieved 4.9%; [Inception-v3] reaches 3.46%. > How well do humans do on ImageNet Challenge? There's a [blog post] by Andrej Karpathy who attempted to measure his own performance. He reached |