the models in deep-learning on a little corpus

I have a little corpus (around 450 observations with approximately 50 words) with domain specific words. I have to classify each observation with a target variable with 5 classes. I tokenized and did the preprocess on my text and now I want to do the classification. I tried random forest and perceptron and I get an accuracy around 0.75 which is pretty good!! I saw on the web deep learning was a good tool to work with when we have textual data (that's why I tried perceptron) but I'm pretty new in this field.

Do you have any idea which model in deep learning is good considering my corpus?