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vit-base-patch16-224-dmae-va-U5-100bcont
Augusto777/vit-base-patch16-224-dmae-va-U5-100bcont
vit-base-patch16-224-dmae-va-U5-100bcont is a image classification model from Augusto777. Use it when you need a label for an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- Model type
- vit
- Access
- Public
- Created
- Apr 25, 2024
- Updated
- Apr 25, 2024
- SHA
- 1e88317a
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-dmae-va-U5-100bcont
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5453
- Accuracy: 0.8667
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: 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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9 | 7 | 0.5397 | 0.85 |
| 0.3809 | 1.94 | 15 | 0.5212 | 0.85 |
| 0.316 | 2.97 | 23 | 0.5690 | 0.8 |
| 0.2892 | 4.0 | 31 | 0.6506 | 0.7667 |
| 0.2892 | 4.9 | 38 | 0.5529 | 0.8333 |
| 0.2127 | 5.94 | 46 | 0.4987 | 0.8333 |
| 0.1712 | 6.97 | 54 | 0.5859 | 0.8167 |
| 0.1539 | 8.0 | 62 | 0.5937 | 0.8 |
| 0.1539 | 8.9 | 69 | 0.5103 | 0.8333 |
| 0.1378 | 9.94 | 77 | 0.6844 | 0.7833 |
| 0.1144 | 10.97 | 85 | 0.5357 | 0.85 |
| 0.1055 | 12.0 | 93 | 0.6695 | 0.8 |
| 0.1093 | 12.9 | 100 | 0.5593 | 0.85 |
| 0.1093 | 13.94 | 108 | 0.5453 | 0.8667 |
| 0.0956 | 14.97 | 116 | 0.6144 | 0.85 |
| 0.1057 | 16.0 | 124 | 0.5067 | 0.8333 |
| 0.0907 | 16.9 | 131 | 0.6570 | 0.8 |
| 0.0907 | 17.94 | 139 | 0.5343 | 0.8667 |
| 0.1184 | 18.97 | 147 | 0.5516 | 0.8667 |
| 0.1014 | 20.0 | 155 | 0.8173 | 0.7667 |
| 0.0997 | 20.9 | 162 | 0.6839 | 0.8167 |
| 0.1067 | 21.94 | 170 | 0.5552 | 0.8667 |
| 0.1067 | 22.97 | 178 | 0.5475 | 0.8667 |
| 0.082 | 24.0 | 186 | 0.5567 | 0.85 |
| 0.0852 | 24.9 | 193 | 0.6374 | 0.8167 |
| 0.0815 | 25.94 | 201 | 0.6486 | 0.8167 |
| 0.0815 | 26.97 | 209 | 0.6218 | 0.8167 |
| 0.0917 | 27.1 | 210 | 0.6209 | 0.8167 |
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
- Created
- Apr 25, 2024
- Updated
- Apr 25, 2024