Comments (1)
The discrepancy is reasonable as the dataset used for training has additional augmentations that are not present in the transforms for the validation set. Using the same transforms for both the train and validation sets leads to the expected pattern of training accuracy being higher than validation accuracy.
from vit-pytorch.
Related Issues (20)
- Not able to load ViT-H_14 HOT 1
- Testing HOT 2
- Why is the addition of convolution useless
- how train from scratch on cifar100?
- How to set the number of epoch?
- [ Softmax() missing ]
- Why the model gives the same logits for both the classes? HOT 2
- Why we need to calculate residual connections when visualize attention maps? HOT 3
- Loss doesn't drop in the example
- Missing check of when (step+1) == len(trainset) in gradient_accumulation
- apex version? HOT 1
- Docker HOT 1
- Could you please provide me a test codes?
- how can I use the output .bin file again ? HOT 2
- How to convert Pytorch model checkpoint in .bin -> .npz ?
- <urlopen error [Errno -2] Name or service not known> HOT 1
- Patch size and n_patches calculation issue when grid is specified HOT 2
- Can FasterTransformer be used on Jetson Orin series Chips?
- For torch.distributed.launch ARG --local_rank should be --local-rank
- reconstruction task
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from vit-pytorch.