metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-brain-alzheimer-detection
results: []
vit-base-brain-alzheimer-detection
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: 0.2428
- Accuracy: 0.9508
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: 2e-05
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9772 | 0.7812 | 200 | 0.9400 | 0.5801 |
| 0.7451 | 1.5625 | 400 | 0.7947 | 0.6553 |
| 0.5701 | 2.3438 | 600 | 0.7642 | 0.7236 |
| 0.3704 | 3.125 | 800 | 0.5532 | 0.7744 |
| 0.2906 | 3.9062 | 1000 | 0.4423 | 0.8555 |
| 0.1636 | 4.6875 | 1200 | 0.3226 | 0.9004 |
| 0.0837 | 5.4688 | 1400 | 0.3483 | 0.9023 |
| 0.0368 | 6.25 | 1600 | 0.2423 | 0.9395 |
| 0.063 | 7.0312 | 1800 | 0.3091 | 0.9277 |
| 0.047 | 7.8125 | 2000 | 0.3907 | 0.9023 |
| 0.0127 | 8.5938 | 2200 | 0.2002 | 0.9561 |
| 0.0102 | 9.375 | 2400 | 0.3001 | 0.9307 |
| 0.0086 | 10.1562 | 2600 | 0.1998 | 0.9512 |
| 0.0073 | 10.9375 | 2800 | 0.1932 | 0.9590 |
| 0.0064 | 11.7188 | 3000 | 0.1988 | 0.9561 |
| 0.0056 | 12.5 | 3200 | 0.1993 | 0.9580 |
| 0.0049 | 13.2812 | 3400 | 0.2047 | 0.9590 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1