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vit-dropout-v5
sharren/vit-dropout-v5
vit-dropout-v5 is a image classification model from sharren. 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
- Feb 26, 2024
- Updated
- Feb 26, 2024
- SHA
- 7f015440
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. -->
vit-dropout-v5
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5648
- Accuracy: 0.8670
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6877 | 1.56 | 500 | 0.8813 | 0.7185 |
| 0.509 | 3.12 | 1000 | 0.5928 | 0.7834 |
| 0.4729 | 4.67 | 1500 | 0.5438 | 0.8015 |
| 0.5043 | 6.23 | 2000 | 0.5439 | 0.8102 |
| 0.456 | 7.79 | 2500 | 0.4814 | 0.8246 |
| 0.2336 | 9.35 | 3000 | 0.5169 | 0.8452 |
| 0.3513 | 10.9 | 3500 | 0.4543 | 0.8527 |
| 0.2456 | 12.46 | 4000 | 0.5365 | 0.8583 |
| 0.2029 | 14.02 | 4500 | 0.5582 | 0.8489 |
| 0.0715 | 15.58 | 5000 | 0.5121 | 0.8633 |
| 0.0561 | 17.13 | 5500 | 0.5564 | 0.8702 |
| 0.035 | 18.69 | 6000 | 0.5648 | 0.8670 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Feb 26, 2024
- Updated
- Feb 26, 2024