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vit-base-16-thesis-demo-PH2
ahishamm/vit-base-16-thesis-demo-PH2
vit-base-16-thesis-demo-PH2 is a image classification model from ahishamm. 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
- Dec 5, 2023
- Updated
- Dec 5, 2023
- SHA
- 70e6e134
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-base-16-thesis-demo-PH2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the ahishamm/PH2_db_enhanced_balanced dataset. It achieves the following results on the evaluation set:
- Loss: 0.0761
- Accuracy: 0.9844
- Recall: 0.9844
- F1: 0.9844
- Precision: 0.9844
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: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 | Precision |
|---|---|---|---|---|---|---|---|
| 0.044 | 2.5 | 50 | 0.0761 | 0.9844 | 0.9844 | 0.9844 | 0.9844 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Dec 5, 2023
- Updated
- Dec 5, 2023