metadata
library_name: transformers
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-brain-abnormalities-classification
results: []
swin-brain-abnormalities-classification
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1730
- Accuracy: 0.9531
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8641 | 0.9892 | 23 | 0.5282 | 0.7739 |
| 0.4526 | 1.9785 | 46 | 0.2441 | 0.8978 |
| 0.271 | 2.9677 | 69 | 0.1764 | 0.9313 |
| 0.2309 | 4.0 | 93 | 0.1976 | 0.9380 |
| 0.1705 | 4.9892 | 116 | 0.1841 | 0.9414 |
| 0.1789 | 5.9785 | 139 | 0.1264 | 0.9531 |
| 0.1442 | 6.9677 | 162 | 0.2048 | 0.9397 |
| 0.1463 | 8.0 | 186 | 0.1362 | 0.9564 |
| 0.122 | 8.9892 | 209 | 0.1399 | 0.9514 |
| 0.1157 | 9.9785 | 232 | 0.1184 | 0.9615 |
| 0.1089 | 10.9677 | 255 | 0.1848 | 0.9481 |
| 0.1062 | 12.0 | 279 | 0.1380 | 0.9581 |
| 0.0969 | 12.9892 | 302 | 0.1658 | 0.9548 |
| 0.0824 | 13.9785 | 325 | 0.1736 | 0.9548 |
| 0.0768 | 14.8387 | 345 | 0.1730 | 0.9531 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0