language:
- ru
tags:
- toxic comments classification
licenses:
- cc-by-nc-sa
General concept of the model
This model is trained on the dataset of inappropriate messages of the Russian language. The concept of inappropriateness is described in this article presented at the workshop for Balto-Slavic NLP at the EACL-2021 conference. Please note that this article describes the first version of the dataset, while the model is trained on the extended version of the dataset open-sourced on our GitHub or on kaggle. The properties of the dataset is the same as the one described in the article, the only difference is the size.
The model was trained, validated and tested only on the samples with 100% confidence, which allowed to get the following metrics on test set:
| precision | recall | f1-score | support | |
|---|---|---|---|---|
| 0 | 0.92 | 0.93 | 0.93 | 7839 |
| 1 | 0.80 | 0.76 | 0.78 | 2726 |
| accuracy | 0.89 | 10565 | ||
| macro avg | 0.86 | 0.85 | 0.85 | 10565 |
| weighted avg | 0.89 | 0.89 | 0.89 | 10565 |
Licensing Information
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Citation
If you find this repository helpful, feel free to cite our publication:
@inproceedings{babakov-etal-2021-bsnlp,
title = "Detecting Inappropriate Messages on Sensitive Topics that Could Harm a Company's Reputation",
author = "Babakov, Nikolay and Logacheva, Varvara and Kozlova, Olga and Semenov, Nikita and Panchenko, Alexander",
booktitle = "To appear in the Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
month = April,
year = "2021",
address = "Kyiv, Ukraine"
}