Downloads · 30 days
1.5K
0% of all-time downloads
vit-base-patch16-224-in21k-finetuned-cifar10
aaraki/vit-base-patch16-224-in21k-finetuned-cifar10
vit-base-patch16-224-in21k-finetuned-cifar10 is a image classification model from aaraki. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
525K
Public
Repo size
687 MB
Likes
13
Public
Repo makeup
Click a slice to open those files.
.bin343 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Mar 30, 2022
- Updated
- Mar 30, 2022
- SHA
- 63acc43b
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
vit-base-patch16-224-in21k-finetuned-cifar10
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2564
- Accuracy: 0.9788
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4291 | 1.0 | 390 | 0.2564 | 0.9788 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Hf Inference
- live
- Created
- Mar 30, 2022
- Updated
- Mar 30, 2022