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您好,我在复现EasyQuant的算法之后,发现确实在验证集上calibration以及easyquant可以获得更好的后量化性能。但是在训练集上来做calibration和easyquant则效果非常非常不稳定,经常eq之后的模型精度还比不上calibration。作者有做过类似的尝试吗?
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都是数据,应该不会有这样的差异,你需要仔细检查一下你的代码,或者在其它任务上尝试一下来做为对比。
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你可以检查一下log文件,关注下量化的cos相似度在哪一层出现明显的下降,可以适当调整搜索的范围和粒度
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您好,我在复现EasyQuant的算法之后,发现确实在验证集上calibration以及easyquant可以获得更好的后量化性能。但是在训练集上来做calibration和easyquant则效果非常非常不稳定,经常eq之后的模型精度还比不上calibration。作者有做过类似的尝试吗?
The text was updated successfully, but these errors were encountered: