I am currently fine-tuning a LLM with a custom QA dataset, and was wondering whether there would be a significant difference whether I ran QLoRA fine-tuning with a model initialized with AutoModelForCausalLM and a model initialized with AutoModelForQuestionAnswering. If there does exist a significant difference, which of the two is preferrable?
For additional context, the dataset I will be fine-tuning with consists of three columns: question, context, and answer. The three columns are then formatted with a prompt along the lines of
### Instruction
Use the context below to generate an answer to the provided question. If the context does not contain sufficient information, state that an answer could not be found.
### Context
{context}
### Question
{question}
### Response
{response}