train.csv | 3 MB | |
test.csv | 1 MB | |
sample_submission.csv | 1 MB |
The dataset presented here was collected from one of the public film rating resources. We have selected the 6 most popular movie genres and invite you to try to predict them.
train.csv
- The training set, comprising the movie_name
, movie_description
and target
of each film, the latter of which is the genre of the film. target
comprise the target for the competition. test.csv
- For the test data we give only the movie_description
of an film together with its movie_name
.sample_submission.csv
- A submission file in the correct format.You can download the dataset by following the link.
Submissions are scored using Accuracy error:
where N is the number of samples in the test dataset.
For each row in the test set, you need to predict one of the 6 movie genres. The file should contain a header and have the following format:
id,target
133530575988338041546938011932244933990,5
133530621940672299820253816187736128870,2
133530687700047186659654018829214907750,3
133531296172335296209766737246753488230,0
...
git clone https://github.com/e0xextazy/nlp_huawei_new2_task.git
cd nlp_huawei_new2_task/
python3.7 -m venv venv
source venv/bin/activate
./setup/setup_tf_idf_logreg.sh
./setup/setup_catboost.sh
./setup/setup_lstm.sh
./setup/setup_transformers.sh
./setup/download_data.sh
Copy of the contributing.md
.
How to make a pull request.
git checkout -b issue-id-short-name
;git push
;master
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