ruidan/aspect-level-sentiment

Code and dataset for ACL2018 paper "Exploiting Document Knowledge for Aspect-level Sentiment Classification"

aspect-level-sentiment's Issues

ValueError: All input arrays (x) should have the same number of samples. Got array shapes: [(2, 74), (2, 18), (32, 572)]

Hello, I have already run your program and I get the following error when running the second loop in train.py. I have been watching for a long time, but I can't find a mistake. Can you help me see why this is? Thank you

missing a few training data ?

Thanks for sharing.
From the preprocessed data, I realized the counts of examples (from my script) are not the same as reported in the paper.

For example, the training data of SemEval 2014 is like this:
lt Counter({'positive': 987, 'negative': 866, 'neutral': 460})
res Counter({'positive': 2164, 'negative': 805, 'neutral': 633})

Did I make any mistake?

error when runing the code

Hi,

I got this error when trying to run the train.py file

TypeError: add_weight() got multiple values for keyword argument 'name'

ANy ideas plz

thank u

About the precision

hello, I modified the code to run with python3 and it can run, but I can't get the same precision you mentioned in the paper, the precision just was 50%, when I adjust the learning rate the precision improve to 67% but still has a gap with your experiment. I used your preprocessed_data. Do you have any idea about improving the precision? thank you!

Predicting output for new sentences with the new model

Hi,
I tried retraining the model, it went on training and showed the loss during every epoch but at the end of the training it didn't save anything (Model or Word vector file), which I could use for further predictions. Also is there a way to use model and find the sentiment of the input sentence?

ValueError: All input arrays (x) should have the same number of samples. Got array shapes: [(2, 74), (2, 18), (32, 572)]

Hello, I have already run your program, and the error shown in the title appears when train.py runs the second args.epochs loop. I don't know why the number of all input array (x) samples has changed. I have been watching for a long time, but I can't find a mistake. Can you help me see why this is? Thank you