Comments (3)
Hi Amazedan,
Firstly, you can assess the performance of the trained model by evaluating it on all test samples and obtaining the loss values for each sample. Afterward, you can utilize matplotlib to create a histogram depicting the distribution of the loss values.
from erasing-attention-consistency.
Thank you! I think I understand how to draw now.
from erasing-attention-consistency.
Hello, author. I'd like to confirm with you: are we calculating the loss values on the test set? If so, how do we differentiate between noisy and clean samples?
from erasing-attention-consistency.
Related Issues (20)
- About the pre-trained models HOT 2
- Memory leak HOT 1
- Reproduce the performance of the paper on AffectNet and FERPlus HOT 1
- 数据集问题和运行问题
- 你好,作者,能提供一下基础resnet50训练到88.75的代码么?
- log
- Feature visualization HOT 2
- MobileNet pretrained model HOT 4
- help FERplus HOT 1
- Changing backbone to ResNet-18 HOT 2
- Pre-trained model? HOT 1
- Help reproduce rafdb HOT 2
- help reproduce AffectNet and FERplus HOT 2
- FERPlus复现问题
- Question about use bias on linear layer
- Question about the reuse of view1 features for CAM computation HOT 2
- Hi, about the training HOT 1
- dataset? HOT 2
- AffectNet performance
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from erasing-attention-consistency.