What could cause a Convolutional Neural Network to fail to converge?
I am using Tensorflow's iris_training model with some of my own data.
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=0.00001), n_classes=11, model_dir="/tmp/iris_model")
Can anyone give me any advice on how to modify my network layers, data size, etc to improve my results, given that I have already adjusted the optimizer, put a zero for the learning rate, and opted not to use an optimizer?