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/home/ubuntu/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
INFO:root:Ngrams range for the training run : 1
INFO:root:Loading Training data
INFO:root:Opening file /dev/shm/fastText/data/yelp_review_polarity.train for reading input
INFO:root:Loading Test data
INFO:root:Opening file /dev/shm/fastText/data/yelp_review_polarity.test for reading input
INFO:root:Vocabulary size: 464402
INFO:root:Training data converting to sequences...
INFO:root:Done! Sequence conversion Time=109.57s, #Sentences=560000
INFO:root:Done! Sequence conversion Time=93.96s, #Sentences=38000
INFO:root:Encoding labels
INFO:root:Label mapping:{'__label__1': 0, '__label__2': 1}
INFO:root:Done! Preprocessing Time=20.78s, #Sentences=560000
INFO:root:Done! Preprocessing Time=14.98s, #Sentences=38000
INFO:root:Number of labels: 2
INFO:root:Initializing network
INFO:root:Running Training on ctx:gpu(0)
INFO:root:Number of output units in the last layer :1
INFO:root:Network initialized
INFO:root:Changing the loss function to sigmoid since its Binary Classification
INFO:root:Loss function for training:SigmoidBinaryCrossEntropyLoss(batch_axis=0, w=None)
INFO:root:Starting Training!
INFO:root:Training on 560000 samples and testing on 38000 samples
INFO:root:Number of batches for each epoch : 35000.0, Display cadence: 3500
INFO:root:Epoch : 0, Batches complete :0
INFO:root:Epoch : 0, Batches complete :3500
INFO:root:Epoch : 0, Batches complete :7000
INFO:root:Epoch : 0, Batches complete :10500
INFO:root:Epoch : 0, Batches complete :14000
INFO:root:Epoch : 0, Batches complete :17500
INFO:root:Epoch : 0, Batches complete :21000
INFO:root:Epoch complete :0, Computing Accuracy
INFO:root:Epochs completed : 0 Test Accuracy: 0.9038157894736842, Test Loss: 0.3171945011025587
INFO:root:Epoch : 1, Batches complete :0
INFO:root:Epoch : 1, Batches complete :3500
INFO:root:Epoch : 1, Batches complete :7000
INFO:root:Epoch : 1, Batches complete :10500
INFO:root:Epoch : 1, Batches complete :14000
INFO:root:Epoch : 1, Batches complete :17500
INFO:root:Epoch : 1, Batches complete :21000
INFO:root:Epoch complete :1, Computing Accuracy
INFO:root:Epochs completed : 1 Test Accuracy: 0.9285263157894736, Test Loss: 0.22869067299865983
INFO:root:Epoch : 2, Batches complete :0
INFO:root:Epoch : 2, Batches complete :3500
INFO:root:Epoch : 2, Batches complete :7000
INFO:root:Epoch : 2, Batches complete :10500
INFO:root:Epoch : 2, Batches complete :14000
INFO:root:Epoch : 2, Batches complete :17500
INFO:root:Epoch : 2, Batches complete :21000
INFO:root:Epoch complete :2, Computing Accuracy
INFO:root:Epochs completed : 2 Test Accuracy: 0.9318421052631579, Test Loss: 0.2200586399126942
INFO:root:Epoch : 3, Batches complete :0
INFO:root:Epoch : 3, Batches complete :3500
INFO:root:Epoch : 3, Batches complete :7000
INFO:root:Epoch : 3, Batches complete :10500
INFO:root:Epoch : 3, Batches complete :14000
INFO:root:Epoch : 3, Batches complete :17500
INFO:root:Epoch : 3, Batches complete :21000
INFO:root:Epoch complete :3, Computing Accuracy
INFO:root:Epochs completed : 3 Test Accuracy: 0.9379736842105263, Test Loss: 0.19040078702274849
INFO:root:Epoch : 4, Batches complete :0
INFO:root:Epoch : 4, Batches complete :3500
INFO:root:Epoch : 4, Batches complete :7000
INFO:root:Epoch : 4, Batches complete :10500
INFO:root:Epoch : 4, Batches complete :14000
INFO:root:Epoch : 4, Batches complete :17500
INFO:root:Epoch : 4, Batches complete :21000
INFO:root:Epoch complete :4, Computing Accuracy
INFO:root:Epochs completed : 4 Test Accuracy: 0.9387894736842105, Test Loss: 0.1793042681057397
INFO:root:Epoch : 5, Batches complete :0
INFO:root:Epoch : 5, Batches complete :3500
INFO:root:Epoch : 5, Batches complete :7000
INFO:root:Epoch : 5, Batches complete :10500
INFO:root:Epoch : 5, Batches complete :14000
INFO:root:Epoch : 5, Batches complete :17500
INFO:root:Epoch : 5, Batches complete :21000
INFO:root:Epoch complete :5, Computing Accuracy
INFO:root:Epochs completed : 5 Test Accuracy: 0.9391052631578948, Test Loss: 0.18214678083977748
INFO:root:Epoch : 6, Batches complete :0
INFO:root:Epoch : 6, Batches complete :3500
INFO:root:Epoch : 6, Batches complete :7000
INFO:root:Epoch : 6, Batches complete :10500
INFO:root:Epoch : 6, Batches complete :14000
INFO:root:Epoch : 6, Batches complete :17500
INFO:root:Epoch : 6, Batches complete :21000
INFO:root:Epoch complete :6, Computing Accuracy
INFO:root:Epochs completed : 6 Test Accuracy: 0.9394473684210526, Test Loss: 0.17967952292745912
INFO:root:Epoch : 7, Batches complete :0
INFO:root:Epoch : 7, Batches complete :3500
INFO:root:Epoch : 7, Batches complete :7000
INFO:root:Epoch : 7, Batches complete :10500
INFO:root:Epoch : 7, Batches complete :14000
INFO:root:Epoch : 7, Batches complete :17500
INFO:root:Epoch : 7, Batches complete :21000
INFO:root:Epoch complete :7, Computing Accuracy
INFO:root:Epochs completed : 7 Test Accuracy: 0.9392631578947368, Test Loss: 0.17987134655604234
INFO:root:Epoch : 8, Batches complete :0
INFO:root:Epoch : 8, Batches complete :3500
INFO:root:Epoch : 8, Batches complete :7000
INFO:root:Epoch : 8, Batches complete :10500
INFO:root:Epoch : 8, Batches complete :14000
INFO:root:Epoch : 8, Batches complete :17500
INFO:root:Epoch : 8, Batches complete :21000
INFO:root:Epoch complete :8, Computing Accuracy
INFO:root:Epochs completed : 8 Test Accuracy: 0.9397105263157894, Test Loss: 0.17990990590706102
INFO:root:Epoch : 9, Batches complete :0
INFO:root:Epoch : 9, Batches complete :3500
INFO:root:Epoch : 9, Batches complete :7000
INFO:root:Epoch : 9, Batches complete :10500
INFO:root:Epoch : 9, Batches complete :14000
INFO:root:Epoch : 9, Batches complete :17500
INFO:root:Epoch : 9, Batches complete :21000
INFO:root:Epoch complete :9, Computing Accuracy
INFO:root:Epochs completed : 9 Test Accuracy: 0.9394736842105263, Test Loss: 0.1796451361074455
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