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vit-base-patch16-224-ve-U11-b-24
Augusto777/vit-base-patch16-224-ve-U11-b-24
vit-base-patch16-224-ve-U11-b-24 is a image classification model from Augusto777. 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
- Jun 12, 2024
- Updated
- Jun 12, 2024
- SHA
- 16958568
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-patch16-224-ve-U11-b-24
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: 0.4436
- Accuracy: 0.9130
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: 5.5e-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: 0.05
- num_epochs: 24
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.92 | 6 | 1.3798 | 0.5435 |
| 1.3792 | 2.0 | 13 | 1.3091 | 0.6522 |
| 1.3792 | 2.92 | 19 | 1.2227 | 0.5870 |
| 1.2783 | 4.0 | 26 | 1.1263 | 0.6087 |
| 1.1226 | 4.92 | 32 | 1.0466 | 0.6522 |
| 1.1226 | 6.0 | 39 | 0.9854 | 0.5870 |
| 0.9881 | 6.92 | 45 | 0.9303 | 0.6957 |
| 0.8707 | 8.0 | 52 | 0.8806 | 0.7826 |
| 0.8707 | 8.92 | 58 | 0.8234 | 0.7826 |
| 0.7604 | 10.0 | 65 | 0.7159 | 0.8261 |
| 0.6452 | 10.92 | 71 | 0.6929 | 0.8478 |
| 0.6452 | 12.0 | 78 | 0.6491 | 0.8696 |
| 0.5576 | 12.92 | 84 | 0.5924 | 0.8478 |
| 0.4708 | 14.0 | 91 | 0.5551 | 0.8478 |
| 0.4708 | 14.92 | 97 | 0.6354 | 0.8043 |
| 0.422 | 16.0 | 104 | 0.5130 | 0.8696 |
| 0.3546 | 16.92 | 110 | 0.5302 | 0.8696 |
| 0.3546 | 18.0 | 117 | 0.4436 | 0.9130 |
| 0.3353 | 18.92 | 123 | 0.5621 | 0.8261 |
| 0.3106 | 20.0 | 130 | 0.4912 | 0.8696 |
| 0.3106 | 20.92 | 136 | 0.4747 | 0.8913 |
| 0.312 | 22.0 | 143 | 0.4603 | 0.8913 |
| 0.312 | 22.15 | 144 | 0.4598 | 0.8913 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 12, 2024
- Updated
- Jun 12, 2024