zyh-uaiaaaa / Erasing-Attention-Consistency

Official implementation of the ECCV2022 paper: Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
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Changing backbone to ResNet-18 #19

Open 1emonx opened 10 months ago

1emonx commented 10 months ago

'Changing backbone to ResNet-18 should first tune the learning rate in order to acquire high classification accuracy. More details can be found in the closed issues.' 您好,我浏览了下关闭的问题没有找到相关的内容。当更换backbone后,相关学习率该怎样调整呢?

1emonx commented 10 months ago

请问为什么我直接使用您提供的代码,模型结构方面没有做任何修改,并直接使用了链接中提供的ResNet50的预训练模型,在clean标签上训练得到的测试集的最好结果仅为82%左右?

zyh-uaiaaaa commented 9 months ago

学习率需要从1e-4调整到2e-4。 这个不太可能,估计是你代码某个地方出了问题,或者标签没有读对,82%的准确率过于低了。 你可以参考一下我对其他人问题的回复,如下: “I have re-run my code without making any changes. Using the pre-trained ResNet-50 model, it easily achieved an accuracy of 90.35% and the best accuracy recorded was 90.51%, without any label noise. Could you please either re-run my code or provide me with your log file to assist me in identifying the reason behind this?”