Is there any classifier that works best in general for NLP based projects? I've written a program to analyse a given piece of text from a website and make conclusary classifications as to its validity. The code basically vectorizes the description (taken from the HTML of a given webpage in real time) and takes in a few inputs from that as features to make its decisions. There are some more features like the domain of the website and some keywords I've explicitly counted.

The highest accuracy I've been able to achieve is with a RandomForestClassifier, (>90%). I'm not sure what I can do to make this accuracy better except incorporating a more sophisticated model. I tried using an MLP but for no set of hyperparameters does it seem to exceed the previous accuracy. I have around 2000 datapoints available for training.

Is there any classifier that works best for such projects? Does anyone have any suggestions as to how I can bring about improvements? (If anything needs to be elaborated, I'll do so.)

Any suggestions on how I can improve on this project in general? Should I include the text on a webpage as well? How should I do so? I tried going through a few sites, but the next doesn't seem to be contained in any specific element whereas the description is easy to obtain from the HTML. Any help?

What else can I take as features? If anyone could suggest any creative ideas, I'd really appreciate it.
The accuracy depends on various factors. Might not always be the algorithm. For example a cleaner data with a poor algorithm might still give better results and vice versa. 

What are the preprocessing techniques you are using? This preprocessing techniques article is a good starting point for html data. And by vectorising I assume you mean word2vec, use a pre-trained word2vec model. Like google's word2vec model it's trained on a lot of data(about 100 billion words). 

LSTM performs good whenever the intent of the sentence is important. Check out this.
Ram hit Vijay and Vijay hit Ram, might mean the same to most algorithms. Example, Naive Bayes.