Comments (4)
主要结果是test结果,val只用来选超参。report val的表会在图注里单独注明了这是val的结果
from long-tailed-recognition.pytorch.
主要结果是test结果,val只用来选超参。report val的表会在图注里单独注明了这是val的结果
请问imagenet_LT的结果为所有epoch中最优结果还是最后一个epoch的结果
from long-tailed-recognition.pytorch.
主要结果是test结果,val只用来选超参。report val的表会在图注里单独注明了这是val的结果
请问imagenet_LT的结果为所有epoch中最优结果还是最后一个epoch的结果
测试test集用的模型是val上最好的epoch。
from long-tailed-recognition.pytorch.
主要结果是test结果,val只用来选超参。report val的表会在图注里单独注明了这是val的结果
请问imagenet_LT的结果为所有epoch中最优结果还是最后一个epoch的结果
测试test集用的模型是val上最好的epoch。
好的,明白了,感谢
from long-tailed-recognition.pytorch.
Related Issues (20)
- 关于cifar10训练精度问题 HOT 2
- 关于lvis1.0中计算d HOT 2
- Could you please provide lvis checkpoint and training log? HOT 2
- LVIS training bug: TypeError: can't pickle _thread.RLock objects HOT 2
- imagenet是2012还是2014呢? HOT 1
- imagenet-LT HOT 2
- Question about methods Cosine and Capsule in the paper HOT 3
- 请问detection中rcnn head的cls是不是做了2次softmax操作? HOT 6
- Moving average for d_hat HOT 1
- RuntimeError: Given input size: (2048x1x1). Calculated output size: (2048x-5x-5). Output size is too small HOT 1
- Migration to multi label long tailed recognition HOT 2
- Cifar Validation set HOT 1
- Focal loss on ImageNet-LT HOT 2
- 关于训练和测试集同是长尾分布时 TDE 有效性的问题? HOT 2
- 论文问题
- 关于统计移动平均特征的代码问题 HOT 1
- 论文求助
- A question regarding the assignment of num_head, tau, alpha and gamma
- Welcome update to OpenMMLab 2.0
- 一个严重的bug
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