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0.50-Train-Test-vit-large
ahmedesmail16/0.50-Train-Test-vit-large
0.50-Train-Test-vit-large is a image classification model from ahmedesmail16. 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, 2024
- Updated
- Jun 21, 2024
- SHA
- 00f4d1cd
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. -->
0.50-Train-Test-vit-large
This model is a fine-tuned version of google/vit-large-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8804
- Accuracy: 0.8098
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.3722 | 0.9825 | 14 | 1.8140 | 0.3758 |
| 1.7117 | 1.9649 | 28 | 0.9446 | 0.7383 |
| 0.3741 | 2.9474 | 42 | 0.8083 | 0.7338 |
| 0.1709 | 4.0 | 57 | 0.7460 | 0.7562 |
| 0.0166 | 4.9825 | 71 | 0.7632 | 0.7763 |
| 0.0087 | 5.9649 | 85 | 0.9165 | 0.7629 |
| 0.013 | 6.9474 | 99 | 0.8161 | 0.7942 |
| 0.0029 | 8.0 | 114 | 0.8216 | 0.7964 |
| 0.0016 | 8.9825 | 128 | 0.8461 | 0.7919 |
| 0.0009 | 9.9649 | 142 | 0.8528 | 0.7919 |
| 0.0007 | 10.9474 | 156 | 0.8539 | 0.8031 |
| 0.0006 | 12.0 | 171 | 0.8586 | 0.8054 |
| 0.0006 | 12.9825 | 185 | 0.8622 | 0.8076 |
| 0.0005 | 13.9649 | 199 | 0.8649 | 0.8098 |
| 0.0005 | 14.9474 | 213 | 0.8677 | 0.8098 |
| 0.0005 | 16.0 | 228 | 0.8706 | 0.8098 |
| 0.0004 | 16.9825 | 242 | 0.8729 | 0.8098 |
| 0.0004 | 17.9649 | 256 | 0.8747 | 0.8098 |
| 0.0004 | 18.9474 | 270 | 0.8764 | 0.8076 |
| 0.0004 | 20.0 | 285 | 0.8776 | 0.8098 |
| 0.0004 | 20.9825 | 299 | 0.8789 | 0.8076 |
| 0.0003 | 21.9649 | 313 | 0.8794 | 0.8098 |
| 0.0003 | 22.9474 | 327 | 0.8801 | 0.8098 |
| 0.0003 | 24.0 | 342 | 0.8804 | 0.8098 |
| 0.0003 | 24.5614 | 350 | 0.8804 | 0.8098 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 21, 2024
- Updated
- Jun 21, 2024