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vit-base-pets
OmAlve/vit-base-pets
vit-base-pets is a image classification model from OmAlve. 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
- Mar 30, 2024
- Updated
- Mar 31, 2024
- SHA
- 934882fd
Base models
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-pets
This model is a fine-tuned version of google/vit-base-patch16-224 on the pcuenq/oxford-pets dataset. It achieves the following results on the evaluation set:
- Loss: 0.3168
- Accuracy: 0.9432
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: 0.0003
- train_batch_size: 128
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5136 | 1.0 | 47 | 1.1031 | 0.8430 |
| 0.5547 | 2.0 | 94 | 0.5232 | 0.9269 |
| 0.4111 | 3.0 | 141 | 0.3988 | 0.9310 |
| 0.3438 | 4.0 | 188 | 0.3553 | 0.9337 |
| 0.298 | 5.0 | 235 | 0.3448 | 0.9296 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 30, 2024
- Updated
- Mar 31, 2024