metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Brain-Tumor-Classification
results: []
Brain-Tumor-Classification
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: 0.1728
- Accuracy: 0.9544
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0978 | 0.99 | 52 | 0.6856 | 0.7602 |
| 0.5021 | 2.0 | 105 | 0.3709 | 0.9041 |
| 0.3131 | 2.99 | 157 | 0.2680 | 0.9281 |
| 0.226 | 4.0 | 210 | 0.2189 | 0.9424 |
| 0.1682 | 4.99 | 262 | 0.2105 | 0.9376 |
| 0.155 | 6.0 | 315 | 0.1873 | 0.9448 |
| 0.127 | 6.99 | 367 | 0.1635 | 0.9568 |
| 0.1227 | 7.92 | 416 | 0.1728 | 0.9544 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2