Skip to content

Compare BERT-based models for document-level sentiment analysis using the SemEval 2017 Twitter dataset.

License

Notifications You must be signed in to change notification settings

williamcorsel/BertEval

Repository files navigation

BertEval

Compare BERT-based models for document-level sentiment analysis using the SemEval 2017 Twitter dataset.

Installation:

Run the following command to install other dependencies

pip install -r requirements.txt

Download the SemEval twitter data from here and place the data from the Subtask A from the GOLD folder into the data/tweets folder.

Running

The main program can be run by the following command:

python main.py train

Compare different preprocessing models using the --preprocess_model flag. Choose between tfidf, bert-base-uncased, or other models from Huggingface. The program compares different 'head' neural models using the generated embeddings.

More options can be seen by using the -h tag.

About

Compare BERT-based models for document-level sentiment analysis using the SemEval 2017 Twitter dataset.

Topics

Resources

License

Stars

Watchers

Forks

Languages