Comments (1)
Hi, @sherrychen127. Thank you for your interest.
The configurations are set as default. Have you ever tried our default settings?
For default settings, we have fixed all random seed so that you should achieve exactly the similar results as ours if you use networks such as C3D, R21D. For R3D, the results in our paper (based on R3D) were trained without fixing all random seed, but they should be very similar.
Another thing is that if you use a different cuda version, there might be some difference in results. (Or the same, I am not sure and have not tried different experimental environment)
If there is still problems with your training process, please pose your training settings here and I can try with your settings to check whether something wired happens in my experimental environment.
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Related Issues (14)
- pretrained SSL weights HOT 2
- repeat和shuffle的准确率都是73.5 HOT 5
- Have the same accuracy HOT 6
- Question about pretraining HOT 1
- pytorch 1.7+
- Has the code of IIC v2 been published HOT 1
- UCF101 action classification result only at 0.68 HOT 6
- 方法泛化 HOT 1
- Runtime Error while running the training script HOT 1
- Backbone not freezed during training of classifier HOT 2
- loss stuck in multi-gpu HOT 3
- Training on hmdb51 HOT 8
- Poor finetuning results HOT 23
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