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
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