---
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-tiny-patch4-window7-224-finetuned-leukemia.v2.2
  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-tiny-patch4-window7-224-finetuned-leukemia.v2.2

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: 0.5507
- Accuracy: 0.7638

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.2349        | 0.9984  | 312  | 0.5575          | 0.7698   |
| 0.2191        | 2.0     | 625  | 0.5572          | 0.7618   |
| 0.2124        | 2.9984  | 937  | 0.5580          | 0.769    |
| 0.2207        | 4.0     | 1250 | 0.5500          | 0.763    |
| 0.2143        | 4.9984  | 1562 | 0.5575          | 0.7652   |
| 0.2191        | 6.0     | 1875 | 0.5486          | 0.7728   |
| 0.2063        | 6.9984  | 2187 | 0.5594          | 0.7615   |
| 0.207         | 8.0     | 2500 | 0.5405          | 0.7695   |
| 0.2273        | 8.9984  | 2812 | 0.5568          | 0.7672   |
| 0.2136        | 10.0    | 3125 | 0.5483          | 0.7728   |
| 0.2184        | 10.9984 | 3437 | 0.5606          | 0.7665   |
| 0.212         | 12.0    | 3750 | 0.5578          | 0.761    |
| 0.1903        | 12.9984 | 4062 | 0.5371          | 0.769    |
| 0.2487        | 14.0    | 4375 | 0.5582          | 0.7645   |
| 0.2025        | 14.9984 | 4687 | 0.5414          | 0.7778   |
| 0.2207        | 16.0    | 5000 | 0.5376          | 0.7685   |
| 0.2012        | 16.9984 | 5312 | 0.5489          | 0.7702   |
| 0.2198        | 18.0    | 5625 | 0.5560          | 0.7752   |
| 0.2171        | 18.9984 | 5937 | 0.5570          | 0.7725   |
| 0.2116        | 20.0    | 6250 | 0.5622          | 0.7625   |
| 0.2162        | 20.9984 | 6562 | 0.5587          | 0.7668   |
| 0.224         | 22.0    | 6875 | 0.5456          | 0.7712   |
| 0.212         | 22.9984 | 7187 | 0.5647          | 0.7652   |
| 0.2084        | 24.0    | 7500 | 0.5533          | 0.7672   |
| 0.2226        | 24.9984 | 7812 | 0.5434          | 0.7705   |
| 0.2173        | 26.0    | 8125 | 0.5738          | 0.7675   |
| 0.2216        | 26.9984 | 8437 | 0.5557          | 0.7672   |
| 0.1918        | 28.0    | 8750 | 0.5502          | 0.7705   |
| 0.199         | 28.9984 | 9062 | 0.5456          | 0.7675   |
| 0.21          | 29.9520 | 9360 | 0.5483          | 0.7715   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1