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vit-base-flowers102
MaulikMadhavi/vit-base-flowers102
vit-base-flowers102 is a image classification model from MaulikMadhavi. 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
- Jan 1, 2024
- Updated
- Jan 1, 2024
- SHA
- 1ad31c52
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-flowers102
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the nelorth/oxford-flowers dataset. It achieves the following results on the evaluation set:
- Loss: 0.0770
- Accuracy: 0.9853
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.5779 | 0.22 | 100 | 2.8895 | 0.7775 |
| 1.2226 | 0.45 | 200 | 1.5942 | 0.9255 |
| 0.606 | 0.67 | 300 | 0.8012 | 0.9529 |
| 0.3413 | 0.89 | 400 | 0.4845 | 0.9706 |
| 0.1571 | 1.11 | 500 | 0.2611 | 0.9814 |
| 0.1237 | 1.34 | 600 | 0.1691 | 0.9784 |
| 0.049 | 1.56 | 700 | 0.1146 | 0.9892 |
| 0.0763 | 1.78 | 800 | 0.1209 | 0.9863 |
| 0.0864 | 2.0 | 900 | 0.1223 | 0.9804 |
| 0.0786 | 2.23 | 1000 | 0.1075 | 0.9833 |
| 0.0269 | 2.45 | 1100 | 0.0919 | 0.9843 |
| 0.0178 | 2.67 | 1200 | 0.0795 | 0.9873 |
| 0.0165 | 2.9 | 1300 | 0.0727 | 0.9873 |
| 0.0144 | 3.12 | 1400 | 0.0784 | 0.9853 |
| 0.0138 | 3.34 | 1500 | 0.0759 | 0.9853 |
| 0.0135 | 3.56 | 1600 | 0.0737 | 0.9863 |
| 0.0123 | 3.79 | 1700 | 0.0770 | 0.9853 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jan 1, 2024
- Updated
- Jan 1, 2024