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用下述代码测试了MMStar: export exp_name=./Qwen2-VL-7B-Instruct export model_name=Qwen2-VL-7B CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 torchrun --master_port=25678 --nproc-per-node=8 run_rh2.py --data MMStar --model ${model_name} --model-path $exp_name --verbose
export exp_name=./Qwen2-VL-7B-Instruct export model_name=Qwen2-VL-7B CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 torchrun --master_port=25678 --nproc-per-node=8 run_rh2.py --data MMStar --model ${model_name} --model-path $exp_name --verbose
本地结果:
OpenCompass榜单结果:
请问可能对不齐的原因有什么呀?这两个结果理论上是会对齐的对吗🤔
The text was updated successfully, but these errors were encountered:
你好,结果由于环境不同(transformers, torch, flash-attn, cuda)等会有不等的数值波动。 您的MMStar结果(59.6)和我们的结果(60.7)差距较小,可以理解为环境不同带来的小范围波动。 如果您有其他问题,欢迎讨论。
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PhoenixZ810
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用下述代码测试了MMStar:
export exp_name=./Qwen2-VL-7B-Instruct export model_name=Qwen2-VL-7B CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 torchrun --master_port=25678 --nproc-per-node=8 run_rh2.py --data MMStar --model ${model_name} --model-path $exp_name --verbose
本地结果:
OpenCompass榜单结果:
请问可能对不齐的原因有什么呀?这两个结果理论上是会对齐的对吗🤔
The text was updated successfully, but these errors were encountered: