Comments (6)
lartpang
commented on June 18, 2024
请先确保使用的依赖库的版本是一样的。正常来讲，cod10k和nc4k这两个大一点的数据集的性能是比较稳定的。
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dante1024
commented on June 18, 2024
请先确保使用的依赖库的版本是一样的。正常来讲，cod10k和nc4k这两个大一点的数据集的性能是比较稳定的。
我是按照您提供的依赖库版本重新安装的环境
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lartpang
commented on June 18, 2024
按照之前的网友的反馈：#1 (comment) ，只要使用相同的版本，性能的复现是没有问题的。
请问您使用的是什么GPU呢？
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dante1024
commented on June 18, 2024
按照之前的网友的反馈：#1 (comment) ，只要使用相同的版本，性能的复现是没有问题的。
请问您使用的是什么GPU呢？
我的gpu是tesla P100
我在想会不会是因为您的代码中只保存最后一个epoch的模型，可能最后一个epoch的模型指标不一定是最好的那个？但是按理说就算是最后一个epoch的模型，跟论文指标差距应该不至于这么大
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lartpang
commented on June 18, 2024
@dante1024
在我的实验中确实存在一定的波动，这和训练策略也有一定的关系，毕竟我这里使用了较大学习率的OneCycle形式的学习率衰减。但是我的试验里在后两个数据集上效果还是比较稳定的。
我实际训练使用的显卡是单块2080Ti，开启了混合精度。
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github-actions
commented on June 18, 2024
Stale issue message
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Related Issues (20)
- '_ConfigDict' object has no attribute 'test' HOT 3
- RuntimeError: unexpected EOF, expected 578749 more bytes. The file might be corrupted. HOT 1
- How to draw figure 1 HOT 1
- 关于HMU模块中论文和代码不一致 HOT 3
- 网络参数 HOT 1
- 关于 multi-scale training 的问题 HOT 2
- I encountered the following error when running, what is going on? HOT 6
- Why does it always occupy gpu:0 when I train on other graphics cards HOT 1
- 如何指定在其他显卡上跑实验？ HOT 1
- 复现问题 HOT 9
- 用COD10K-v3的测试集，指标差距大 HOT 2
- 模型加载问题 HOT 2
- 关于训练数据集处理的问题 HOT 1
- 关于辅助尺度的问题 HOT 2
- 预测图
- 数据集或训练配置 HOT 5
- 论文指标有问题 HOT 5
- 关于模型的一些问题 HOT 4
- Extra scale HOT 1
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