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vit-base-patch16-224-Trial006-YEL_STEM4
sbaner24/vit-base-patch16-224-Trial006-YEL_STEM4
vit-base-patch16-224-Trial006-YEL_STEM4 is a image classification model from sbaner24. 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 21, 2023
- Updated
- Nov 14, 2023
- SHA
- 3560fcd6
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-Trial006-YEL_STEM4
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: 0.0984
- Accuracy: 1.0
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: 60
- eval_batch_size: 60
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 240
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7587 | 0.57 | 1 | 0.6296 | 0.7111 |
| 0.6884 | 1.71 | 3 | 0.7730 | 0.4 |
| 0.6112 | 2.86 | 5 | 0.5194 | 0.8222 |
| 0.5566 | 4.0 | 7 | 0.6194 | 0.6444 |
| 0.5216 | 4.57 | 8 | 0.5428 | 0.6889 |
| 0.4488 | 5.71 | 10 | 0.3884 | 0.8222 |
| 0.4438 | 6.86 | 12 | 0.3301 | 0.8444 |
| 0.3897 | 8.0 | 14 | 0.2362 | 0.9111 |
| 0.3789 | 8.57 | 15 | 0.1942 | 0.9333 |
| 0.3484 | 9.71 | 17 | 0.3995 | 0.8222 |
| 0.2727 | 10.86 | 19 | 0.1636 | 0.9556 |
| 0.209 | 12.0 | 21 | 0.1489 | 0.9556 |
| 0.2253 | 12.57 | 22 | 0.1712 | 0.9111 |
| 0.2407 | 13.71 | 24 | 0.2239 | 0.9111 |
| 0.1615 | 14.86 | 26 | 0.0984 | 1.0 |
| 0.1735 | 16.0 | 28 | 0.1231 | 0.9111 |
| 0.179 | 16.57 | 29 | 0.1203 | 0.9111 |
| 0.1464 | 17.71 | 31 | 0.0422 | 1.0 |
| 0.1444 | 18.86 | 33 | 0.0409 | 1.0 |
| 0.1758 | 20.0 | 35 | 0.0394 | 1.0 |
| 0.199 | 20.57 | 36 | 0.0246 | 1.0 |
| 0.1525 | 21.71 | 38 | 0.0179 | 1.0 |
| 0.1536 | 22.86 | 40 | 0.0441 | 1.0 |
| 0.115 | 24.0 | 42 | 0.0836 | 0.9333 |
| 0.106 | 24.57 | 43 | 0.0654 | 0.9778 |
| 0.1267 | 25.71 | 45 | 0.0285 | 1.0 |
| 0.1264 | 26.86 | 47 | 0.0199 | 1.0 |
| 0.1554 | 28.0 | 49 | 0.0192 | 1.0 |
| 0.1456 | 28.57 | 50 | 0.0195 | 1.0 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 1.12.1
- Datasets 2.12.0
- Tokenizers 0.13.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 21, 2023
- Updated
- Nov 14, 2023