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vit-base-patch16-224-ve-U10-24
Augusto777/vit-base-patch16-224-ve-U10-24
vit-base-patch16-224-ve-U10-24 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 11, 2024
- Updated
- Jun 11, 2024
- SHA
- ad9b09c7
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-U10-24
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: 0.7874
- Accuracy: 0.7647
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 |
|---|---|---|---|---|
| 1.3749 | 0.95 | 15 | 1.2899 | 0.4706 |
| 1.1573 | 1.97 | 31 | 1.0844 | 0.5686 |
| 0.985 | 2.98 | 47 | 0.9140 | 0.6078 |
| 0.7024 | 4.0 | 63 | 0.8578 | 0.6863 |
| 0.5699 | 4.95 | 78 | 0.6802 | 0.7451 |
| 0.3784 | 5.97 | 94 | 0.8856 | 0.7059 |
| 0.2631 | 6.98 | 110 | 0.7526 | 0.7451 |
| 0.2201 | 8.0 | 126 | 0.7924 | 0.7255 |
| 0.1933 | 8.95 | 141 | 0.7874 | 0.7647 |
| 0.1592 | 9.97 | 157 | 0.9583 | 0.6863 |
| 0.154 | 10.98 | 173 | 0.9961 | 0.7059 |
| 0.1531 | 12.0 | 189 | 0.8916 | 0.7451 |
| 0.1153 | 12.95 | 204 | 0.9174 | 0.7451 |
| 0.1154 | 13.97 | 220 | 1.0267 | 0.7059 |
| 0.0922 | 14.98 | 236 | 0.9766 | 0.7255 |
| 0.0901 | 16.0 | 252 | 1.0410 | 0.7255 |
| 0.074 | 16.95 | 267 | 1.1869 | 0.6863 |
| 0.0743 | 17.97 | 283 | 1.1094 | 0.7255 |
| 0.084 | 18.98 | 299 | 1.0520 | 0.7255 |
| 0.0713 | 20.0 | 315 | 1.1213 | 0.7059 |
| 0.061 | 20.95 | 330 | 1.0927 | 0.7451 |
| 0.0669 | 21.97 | 346 | 1.0806 | 0.7255 |
| 0.0654 | 22.86 | 360 | 1.0647 | 0.7255 |
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 11, 2024
- Updated
- Jun 11, 2024