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vit-base-1e-4-randaug
vuongnhathien/vit-base-1e-4-randaug
vit-base-1e-4-randaug is a image classification model from vuongnhathien. 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. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- May 27, 2024
- Updated
- May 27, 2024
- SHA
- 076cae1c
Base models
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-1e-4-randaug
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3104
- Accuracy: 0.9157
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1301 | 1.0 | 275 | 0.5623 | 0.8485 |
| 0.7951 | 2.0 | 550 | 0.4347 | 0.8779 |
| 0.67 | 3.0 | 825 | 0.4100 | 0.8891 |
| 0.5883 | 4.0 | 1100 | 0.3799 | 0.8930 |
| 0.5076 | 5.0 | 1375 | 0.3572 | 0.9002 |
| 0.473 | 6.0 | 1650 | 0.3549 | 0.9026 |
| 0.4056 | 7.0 | 1925 | 0.3523 | 0.9066 |
| 0.387 | 8.0 | 2200 | 0.3339 | 0.9070 |
| 0.3529 | 9.0 | 2475 | 0.3329 | 0.9085 |
| 0.3713 | 10.0 | 2750 | 0.3309 | 0.9093 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- May 27, 2024
- Updated
- May 27, 2024