Downloads · 30 days
7
4% of all-time downloads
vit-animals
wmeynard/vit-animals
vit-animals is a image classification model from wmeynard. 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
179
Public
Parameters
85.9M
2.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors343 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Apr 21, 2025
- Updated
- Apr 21, 2025
- SHA
- 3380a758
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-animals
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the mertcobanov/animals dataset. It achieves the following results on the evaluation set:
- Loss: 0.2444
- Accuracy: 0.9565
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.9211 | 0.4926 | 100 | 2.8644 | 0.8963 |
| 1.7472 | 0.9852 | 200 | 1.6272 | 0.9380 |
| 0.6862 | 1.4778 | 300 | 0.7584 | 0.9519 |
| 0.3567 | 1.9704 | 400 | 0.4741 | 0.9519 |
| 0.167 | 2.4631 | 500 | 0.3281 | 0.9546 |
| 0.1162 | 2.9557 | 600 | 0.2864 | 0.9565 |
| 0.0915 | 3.4483 | 700 | 0.2587 | 0.9528 |
| 0.0847 | 3.9409 | 800 | 0.2444 | 0.9565 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Apr 21, 2025
- Updated
- Apr 21, 2025