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vit-augment-v3
sharren/vit-augment-v3
vit-augment-v3 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 25, 2024
- Updated
- Feb 25, 2024
- SHA
- dcafc062
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-augment-v3
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the SkinCancerClassification dataset. It achieves the following results on the evaluation set:
- Loss: 0.4122
- Accuracy: {'accuracy': 0.8682896379525593}
- Precision: {'precision': 0.7891363629481224}
- Recall: {'recall': 0.702147611641084}
- F1: {'f1': 0.7241023904492959}
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
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3588 | 1.0 | 321 | 0.5097 | {'accuracy': 0.8177278401997503} | {'precision': 0.6458951735407427} | {'recall': 0.6505053236299779} | {'f1': 0.638516645464825} |
| 0.3331 | 2.0 | 642 | 0.4549 | {'accuracy': 0.8445692883895131} | {'precision': 0.7630341246189177} | {'recall': 0.6706409138231197} | {'f1': 0.6927226829652856} |
| 0.2535 | 3.0 | 963 | 0.4268 | {'accuracy': 0.8651685393258427} | {'precision': 0.792673703587323} | {'recall': 0.6988841550092643} | {'f1': 0.7201165886292592} |
| 0.1469 | 4.0 | 1284 | 0.4122 | {'accuracy': 0.8682896379525593} | {'precision': 0.7891363629481224} | {'recall': 0.702147611641084} | {'f1': 0.7241023904492959} |
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 25, 2024
- Updated
- Feb 25, 2024