In this paper, we present our system submission for the EmoContext, the third task of SemEval 2019 workshop. Our solution is a hierarchical recurrent neural network with the ELMo embeddings and regularization through dropout and Gaussian noise. We have decided to focus more on the architecture of the model and various methods rather than on the data preprocessing. We have mainly experimented with two main model architectures: simple and hierarchical LSTM network. We have also examined ensembling of the models and various variants of an ensemble. We have achieved microF1 score of 74.81\%, which is significantly higher than baseline and currently the 19th best submission.