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jiegzhan / multi-class-text-classification-cnn

Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.
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UnboundLocalError: local variable 'path' referenced before assignment #15

Open cocokatta opened 6 years ago

cocokatta commented 6 years ago

Hi,

I was using your model trainer, but with considerably less data than from the given example

  1. Trying to train for 3 classes
  2. Approx. 50 sentences in the training set for each class

and what parameters should I provide in order to make a functioning/effective model.

Normally when I run with the given parameters we get an error, and so we were wondering if there was a better way to go about doing that.

Errors include:

  1. for the following paramters { "num_epochs": 1, "batch_size": 20, "num_filters": 32, "filter_sizes": "3,4,5", "embedding_dim": 50, "l2_reg_lambda": 0.0, "evaluate_every": 200, "dropout_keep_prob": 0.5 } logging.critical('Accuracy on test set is {} based on the best model {}'.format(test_accuracy, path)) UnboundLocalError: local variable 'path' referenced before assignment
jiegzhan commented 6 years ago

try smaller batch_size and evaluate_every