The results of applying standard neural network architectures (CNN, LSTM, and BiLSTM) and the recent BERT models to previously labeled data for sentiment analysis in Russian are described. Two versions of the Russian-language BERT model (RuBERT) and different methods of its application to the problem of sentiment analysis are compared. The state-of-the-art results on the datasets were improved significantly.

中文翻译：

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使用Bert神经网络模型进行俄语情感分析

描述了将标准神经网络体系结构（CNN，LSTM和BiLSTM）和最新的BERT模型应用于先前标记的数据以进行俄语情感分析的结果。比较了俄文BERT模型（RuBERT）的两个版本及其在情感分析问题中的不同应用方法。数据集上的最新结果得到了显着改善。