Hello, I am using BERT on the Sentiment Analysis on Movie Reviews dataset from a past (4y ago) Kaggle competition (https://www.kaggle.com/c/sentiment-analysis-on-movie-reviews). The dataset has around 150K training examples and a public test set (for public leaderboard) of 67K examples.
After running 2 epochs (took me 3h) I got 0.688 score on the public leader board which is in the top 5 on the public leaderboard (private leaderboard is not available anymore). It seems to work but I will try to tune the learning rate to see if I can get better result.
I would like to share this in case someone want to do the same experiment so that we can compare the results.
Is it possible to share your code?
I am also planning to do the same task.
Sorry for the late response. I will put my code somewhere so that I can share, but basically what I did is to follow the classification examples in run_classifier.py (https://github.com/google-research/bert#sentence-and-sentence-pair-classification-tasks) :
- Prepare train.tsv, dev.tsv, and test.tsv files with sentence \tab label format (for test.tsv just put 0 for label)
- Create a sub-class of DataProcessor object for your task (see some other examples in the run_classifier.py file)
- Finally run the script run_classifier.py with the option --task_name to be your defined task.
Hope that helps.
Thanks a lot for the reply.
Very interesting what you are doing.
Can you share your code?
That would be great!
Hi @fabsta ,
Sorry for the late reply.
BERT was one of the option I was considering but haven"t done anything on it yet.
If I do complete it then I may (since it is with a company) share it .
hey @canh can you please share your code i’m working on same project .
it will be grateful
thanks in advance.