Cahya Wirawan

Instead of increasing the batch size, try to reduce the batch size from the default 64 to 32 or smaller until it doesn't crash. If it crash also during the...

Actually I used only 4 newsgroups (alt.atheist, com.graphics, sci.med and soc.religion.christian) for my comparison above. I trained also with all 20 newsgroups, and the accuracy of all classifiers decreased, but...

I checked again my trained data for above comparison using tensorboard, and according to the chart below, I reached the accuracy of between 0.6 and 0.7 after 2 epochs. I...

@aksharma90 The probability can be calculated from the score using softmax function. I added the probability of each output in my latest commit (changes in eval.py). The output of prediction...

Which issues did you get?

The GPU issue in tensorflow has often something todo with its low memory. So try to reduce the batch size from the default 64 to 32 or smaller. If it...

Hi @queirozfcom I checked the code again to get a high accuracy faster. It seems that this is possible if we use a higher learning rate. I added a dynamic...

Hi @raziehaskari maybe you can check this link https://sites.google.com/site/rmyeid/projects/polyglot

@mahsaabazary @bhardwaj-gopika GoogleNews-vectors-negative300.bin is the pre-trained word2vec from google, it should be downloaded separately from: https://drive.google.com/file/d/0B7XkCwpI5KDYNlNUTTlSS21pQmM/edit?usp=sharing

I print out the precision, recall and f1-score only at the end of the test evaluation (using metrics from sklearns): https://github.com/cahya-wirawan/cnn-text-classification-tf/blob/master/eval.py