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vectornet用给的模型在val上的结果是minADE是1.67,测试参数(-l 1 -a -b 256 -e 70-w 16 -c -m -r 0 --log_freq 2 --on_memory True --lr 0.001 -we 20 -luf 5 -ldr 0.9 --adam_weight_decay 0.01 --adam_beta1 0.9 --adam_beta2 0.999)但是自己训练出最好的模型minADE=2.05,在val上测试只调了epoch和we最好是2.03不知道是不是参数出了问题?(-l 1 -a -b 256 -e 70 -w 16 -c -m -r 0 --log_freq 2 --on_memory True --lr 0.001 -we 30 -luf 5 -ldr 0.9 --adam_weight_decay 0.01 --adam_beta1 0.9 --adam_beta2 0.999)。
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Hi,
你可以尝试调整下batch size,据我观察batch size在128或64会效果好一些。
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vectornet用给的模型在val上的结果是minADE是1.67,测试参数(-l 1 -a -b 256 -e 70-w 16 -c -m -r 0 --log_freq 2 --on_memory True --lr 0.001 -we 20 -luf 5 -ldr 0.9 --adam_weight_decay 0.01 --adam_beta1 0.9 --adam_beta2 0.999)但是自己训练出最好的模型minADE=2.05,在val上测试只调了epoch和we最好是2.03不知道是不是参数出了问题?(-l 1 -a -b 256 -e 70 -w 16 -c -m -r 0 --log_freq 2 --on_memory True --lr 0.001 -we 30 -luf 5 -ldr 0.9 --adam_weight_decay 0.01 --adam_beta1 0.9 --adam_beta2 0.999)。
The text was updated successfully, but these errors were encountered: