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Practical Assignment 2: Text multiclass classification: store's review rating

Your task is to classify the store's review rating into 5 classes. The metric is F1-score.

We present you 4 baseline solutions based on logistic regression, catboost, LSTM and Transformers.
You can find them in their respective folders: ./baseline_tfidf_logreg./<catboost_baseline>./baseline_rnn and ./<transformer_baseline> in github repo. Each of these folders contains a file requirements.txt that will help you with the installation of the dependencies.

Please be aware that you are not required to use them. The baselines provided only for kickstart.

You should beat the leaderboard baselines: 

  • The easy baseline has quality 0.65. If you beat it you get 10 points.
  • The hard baseline is 0.68. If you beat this baseline you get 10 point for the task. Good luck!
  • If you will be the first in your group, you'll get 3 bonus points.

test.csv

CSV | 2.72 MB

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train.csv

CSV | 10.78 MB

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sample_submission.csv

CSV | 84.22 KB

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