Using the following with TF .9.0rc0 on 60,000 (train) and 26,000 (test) on or so records with 145 coded columns (1,0) trying to predict 1 or 0 for class identification..
I just had a similar issue @Ismael answer is correct. I just wanted to add to the information that now classifier.fit() has the steps parameter that this parameter behaves differently. It doesn't abort earlier. There is another parameter called max_steps. That behaves as the original steps parameter of TensorFlowDNNClassifier.
In short just use the max_steps parameter on fit() like this:
classifier = skflow.DNNClassifier(...)
classifier.fit(X_train, y_train, max_steps=3000)