Comments (3)
Is the problem that the training accuracy goes up to 100%, but that it does not generalize to the test set?
LeViT was created with ImageNet in mind, and the statistics of ImageNet images are quite different to GTSRB images.
Also, the data augmentation (no crop augmentation, etc) might be ok for ConvNets, but suboptimal for ViT models.
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Hi,
Thank you for your reply, I have tried to adjust the training hyperparameters and data augmentation. The LeVit_128S now can achieve 30% accuracy - 346FPS, and LeViT_192 60% accuracy - FPS 277. While the MobileNetV3 Large can achieve 98.37%-355FPS, GhostNet 1.0 97.26%-275FPS. I use the same training and testing method for 3 models but the LeVit models do not fit my method and I really want to improve. That's why I contact you, I would love to see your model working as expected. :( The benchmark illustrates your LeViT_128s have higher accuracy and speed than both MobileNet and GhostNet. I'm looking forward to your advice.
I wonder whether my training method is correct: I download the Pytorch model of MobileNetV3, GhostNet, and your LeVit then load it with config (large for MobileNetV3, width = 1.0 for GhostNet, default for LeVit_128S/192), and num_classes = 43 for all 3 models. Then I use the training source as above. After that, I save the model and then load it in another script for testing.
(https://colab.research.google.com/drive/1yPpAtsibYw8jkzOarLBhdXnWvJR0Uqlo?usp=sharing#scrollTo=r377ZaaKKImT)
from levit.
Sorry, but I don't know enough about GTSRB to help.
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Related Issues (20)
- DeiT Tiny: You say 76% but paper says HOT 1
- LeViT-128S without distillation 100 epoch training reproduction on 1 GPU HOT 4
- Which tool/method you used to compute FLOPs? HOT 2
- The specific setting (e.g., batch-size) to reproduce the inference speed in Tab.3? HOT 2
- How to reproduce the CPU/Arm inference speed in Table 3? HOT 1
- Error loading model after finetuning. HOT 1
- About the shape of attention_biases HOT 2
- LeViT model settings for Cifar10 HOT 1
- AttributeError: module 'timm.models' has no attribute 'vit_deit_tiny_distilled_patch16_224' HOT 1
- Exporting ONNX failed. HOT 2
- Does levit work on detection/segmentation task? HOT 1
- why "Finetuning with distillation not yet supported"? HOT 1
- Using LeViT model and pretrained weights for object detection on larger resolution HOT 1
- Question about train LeViT-256 HOT 1
- Question about training from Checkpoint.pth HOT 1
- Inference - different output when using different batch size HOT 1
- Question about running the speed_test.py HOT 3
- problem of inference precision HOT 1
- inference speed gets faster from paper v1 to v2 on arxiv HOT 1
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