---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-swin-tiny-patch4-window7-224-finetuned-leukemia.v2.1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.954
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# swin-tiny-patch4-window7-224-swin-tiny-patch4-window7-224-finetuned-leukemia.v2.1

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1379
- Accuracy: 0.954

## 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4215        | 0.9991 | 281  | 0.3880          | 0.8293   |
| 0.3137        | 1.9982 | 562  | 0.2898          | 0.8788   |
| 0.2631        | 2.9973 | 843  | 0.2382          | 0.907    |
| 0.2338        | 4.0    | 1125 | 0.4090          | 0.8575   |
| 0.1834        | 4.9991 | 1406 | 0.2477          | 0.8985   |
| 0.2065        | 5.9982 | 1687 | 0.1331          | 0.9513   |
| 0.1555        | 6.9973 | 1968 | 0.1304          | 0.9473   |
| 0.1521        | 8.0    | 2250 | 0.1837          | 0.9293   |
| 0.1512        | 8.9991 | 2531 | 0.1708          | 0.9405   |
| 0.119         | 9.9911 | 2810 | 0.1379          | 0.954    |


### Framework versions

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