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---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-brain-abnormalities-classification-fold2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-brain-abnormalities-classification-fold2
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0893
- Accuracy: 0.9688
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9549 | 0.9714 | 17 | 0.7206 | 0.7236 |
| 0.5426 | 2.0 | 35 | 0.3207 | 0.8686 |
| 0.3933 | 2.9714 | 52 | 0.2391 | 0.8970 |
| 0.2881 | 4.0 | 70 | 0.2387 | 0.8943 |
| 0.2524 | 4.9714 | 87 | 0.1485 | 0.9444 |
| 0.1997 | 6.0 | 105 | 0.1185 | 0.9566 |
| 0.1746 | 6.9714 | 122 | 0.1188 | 0.9553 |
| 0.1589 | 8.0 | 140 | 0.0990 | 0.9621 |
| 0.1369 | 8.9714 | 157 | 0.1044 | 0.9593 |
| 0.1281 | 10.0 | 175 | 0.0957 | 0.9675 |
| 0.1211 | 10.9714 | 192 | 0.1026 | 0.9607 |
| 0.1233 | 12.0 | 210 | 0.1258 | 0.9499 |
| 0.1141 | 12.9714 | 227 | 0.0861 | 0.9729 |
| 0.1021 | 14.0 | 245 | 0.0945 | 0.9648 |
| 0.1102 | 14.5714 | 255 | 0.0893 | 0.9688 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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