In SEED-Bench-2/model/InternLM_Xcomposer_VL_interface.py, for InternLM_Xcomposer_VL model all choices are added to model input and choice letters ("A.", "B.", "C.", "D.") are used as labels to calculate loss. While for all other models (instructblip, qwen_vl, llava_v2), in their interface code we can see only the question is added to model input, and the text of each choice is used as labels to calculate loss independently.
I wonder why do you use different input format for different models? Will this have large impact on accuracy?
In
SEED-Bench-2/model/InternLM_Xcomposer_VL_interface.py, for InternLM_Xcomposer_VL model all choices are added to model input and choice letters ("A.", "B.", "C.", "D.") are used as labels to calculate loss. While for all other models (instructblip, qwen_vl, llava_v2), in their interface code we can see only the question is added to model input, and the text of each choice is used as labels to calculate loss independently.I wonder why do you use different input format for different models? Will this have large impact on accuracy?