Traditional ML Model or Deep Learning for ~200-300 samples?
The less data you have, the less complex your model can be. Otherwise you will overfit your data. There is not really a good way for me to judge what model is appropriate for you without knowing a lot about your dataset, but I doubt you will get anything sensible from 200 data points with a deep learning model. Try some simpler models like bag-of-words and see whether you overfit. If so, you will just have to collect more data. If not, try models of increasing complexity and see how accurate you can get before overfitting sets in.