Deep-Learning Nan loss reasons
Perhaps too general a question, but can anyone explain what would cause a Convolutional Neural Network to diverge? Specifics: I am using Tensorflow's iris_training model with some of my own data and keep getting ERROR:tensorflow:Model diverged with loss = NaN. Traceback... tensorflow.contrib.learn.python.learn.monitors.NanLossDuringTrainingError: NaN loss during training. Traceback originated with line: tf.contrib.learn.DNNClassifier(feature_columns=feature_columns, hidden_units=[300, 300, 300], #optimizer=tf.train.ProximalAdagradOptimizer(learning_rate=0.001, l1_regularization_strength=0