Training a text classification model on dataset


I have a dataset that I want to train a text classification model on so that it classifies sentences according to the dataset. What are the steps needed to achieve this? Does this require a lot of technical knowledge/computing power?

It depends on the size of the dataset to determine the computing power. Also, if you want to fine tune a large model (LLM/pre-trained) model you may need GPU’s for the same. An estimate can be made after seeing your dataset and the model you want to use.
As far as technical knowledge is concerned, if you know the basics of pytorch I think you should be good to go.