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This is about the CNN model in classification-cifar10. Is it possible to achieve an accuracy above eighty percent by changing the architecture?
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Hi, I am try to use your modified model on cifar100.
But my alexnet's accuracy just can be around 42%; and vgg19_bn just can be 62%around ,63.46% most when the 130 epoch .
May be some parameters I s…
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Thank you for sharing your code. I'm happy to try this seemingly attractive representation learning idea on a different backbone. e.g. ResNet50.
Gladly, you mentioned ResNet50 on Table3 in your pap…
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Setting up diva on a new machine (without conda, but the problem should apply in the conda case as well since the torch version is not pinned and the latest conda version is torch@1.1) we ran into som…
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Hi, I found that if I don't use the preetrained model, the code don't work. So I can't train from scratch? If I need to train with other dataset like Imagenet, or use other backbone like resnet50, ho…
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I'm trying to explain a Cifar10 classification model with CEMExplainer. By messing around with the parameters I got a result for the pertinent negative, but I've been having trouble with getting any r…
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🐛 **Describe the bug**
When creating a new _nc\_benchmark_ or _ni\_benchmark_ I get a `Unsupported dataset: must have a valid targets field or has to be a Tensor Dataset with at least 2 Tensors` erro…
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Hi author,
Thank you for your outstanding work! Recently, I repeated this work. During the training process, I trained epoch 500 on the CIFAR10 dataset using the script 'eval_ckpt_cifar10.sh' provi…
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This PR https://github.com/voxel51/fiftyone/pull/169 updated the behavior of `fiftyone.core.sample.Sample.to_dict()`, which caused the server to have to serialize samples in a non-ideal bson -> str ->…
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Thank you for your work.
I have run your code but I couldn't get the same test error rate as your figure.
My final error rate is 12%.
Is there any trick to run your code?
Thank you very much!