<p>The architectures you mention are really loose <em>families</em> of architecture. Performance depends on the details and (of course) the task. Moreover, the two styles are often combined in various ways, so it isn't really an "either-or" choice.</p>

<p>Nevertheless, at the time of writing the CNN-like <a href="https://arxiv.org/abs/1810.04805" rel="nofollow noreferrer">BERT</a> and RNN-like <a href="https://arxiv.org/abs/1802.05365" rel="nofollow noreferrer">ELMo</a> architectures are popular. Pre-trained models and code are available for both and they both perform well across a variety of tasks, including classification. Why not try them both?</p>
Which architecture of Neural Network gives better accuracy for text classification?
<p>I have tried and searched, found that RNNs give better results. Which to use: LSTMs or GRU or traditional RNN or CNN?</p>