Controlling Text Generation with Sentiment as Attribute

Hello! Thank you for such an amazing tool.

I am trying to implement it for my task: i want model to generate texts according to one of three sentiments: positive, neutral, negative. I am not sure it is a text to text task but it is not a simple style transfer either... I tried preprocessing my df with customised preprocessing function:

The traget field is a text which corresponds to a text column in my dataset (there is also a target column in a dataset which is a sentiment). The prompt has a format of "{target}". I used a model ruGPT3large but the results were not very good n the context of language and the attribute usage (however, the text would differ with different sentiments). Important to mention, the loss does not fall, it stays stable all training process:

What can be a problem here?

So, my task of controllable text generation does not probably suit text2text. However, in your notebooks there is no other preprocessing pipeline, only for text2text. I have read the article on Habr and you had there a generation pipeline 'text-generation-with-prompt'. How should I preprocess data then for this task? Or maybe I should use completely different strategy for the task?