Fine Tuning T5 for comment generation task
Hi everyone!I wanted to fine-tune text generation models such as T5 on a task of conditional comment generation. An example is below :Linkedin post author: ContentfulLinkedin post:Today’s digital content can & should be reusable. To do this, modular content should be used to solve scaling issues through smart content reuse. Read the recent Forrester report to learn more.Linkedin post comments:[Laurel Plimpton] comment: Is this a good resource?Reply to [Laurel Plimpton] comment:Output: Yes, it is a great resource. It explains how to use modular content to solve scaling issues and also offers tips on how to create reusable digital content.I was confused about whether providing everything as the context and asking the model to generate the comments would work or not! GPT-3 is able to generate good responses but I want to achieve the same with open source models. Can anyone help me with how can I fine-tune T5 or any relevant model for this task?Thank you!