Brain_Tumor_Classification
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1012
- Accuracy: 0.9647
- F1: 0.9647
- Recall: 0.9647
- Precision: 0.9647
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
F1 |
Recall |
Precision |
| 0.4856 |
0.99 |
83 |
0.3771 |
0.8444 |
0.8444 |
0.8444 |
0.8444 |
| 0.3495 |
1.99 |
166 |
0.2608 |
0.8949 |
0.8949 |
0.8949 |
0.8949 |
| 0.252 |
2.99 |
249 |
0.1445 |
0.9487 |
0.9487 |
0.9487 |
0.9487 |
| 0.2364 |
3.99 |
332 |
0.1029 |
0.9588 |
0.9588 |
0.9588 |
0.9588 |
| 0.2178 |
4.99 |
415 |
0.1012 |
0.9647 |
0.9647 |
0.9647 |
0.9647 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1
