SarcasmDetection
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How to run this on my own data to get sarcasm result?
Two questions:
I have a CSV with one column that contains tweets.
- how can I run this using your pre-trained weights?
- how can I train this using my own training data? Does having 800 ground truth tweets work in this case? Is there a number of minimum ground truth tweets you would suggest?
https://pastebin.com/wxwbmD16 this took about 1 hour for me. I was wondering how I could use a saved model and don't start training from scratch.
Actually I figured the answer to Q1. I just followed your command and commented this
# uncomment for training
#tr = train_model(train_file, validation_file, word_file_path, split_word_path, emoji_file_path, model_file,
# vocab_file_path, output_file)
What should be the format of the test data, the data I want to run your code on and get result? Should I put it in test folder?
The data should be in the following tab-separated format. In case of tweets, each line should represent one tweet.
ID
Please set the test_file with the path of the tab-separated test data. output_file.analysis will contain the output of the test data.
The data should be in the following tab-separated format. In case of tweets, each line should represent one tweet. IDlabeltext
Please set the test_file with the path of the tab-separated test data. output_file.analysis will contain the output of the test data.
Or can take a look into data handler , and change the way read from files. If you have giving a csv file, just look to those lines with separate by "tab" ,change it to something else like separate by ","