---
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-finetuned-leukemia-08-2024.v1.1
  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: 0.895774647887324
---

<!-- 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-08-2024.v1.1

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: 0.3423
- Accuracy: 0.8958

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3578        | 0.9984 | 312  | 1.7841          | 0.4263   |
| 0.2403        | 2.0    | 625  | 0.9414          | 0.6808   |
| 0.1815        | 2.9984 | 937  | 0.6044          | 0.7784   |
| 0.2062        | 4.0    | 1250 | 0.5284          | 0.7643   |
| 0.1212        | 4.9984 | 1562 | 0.4432          | 0.8488   |
| 0.0723        | 6.0    | 1875 | 0.8276          | 0.7925   |
| 0.0656        | 6.9984 | 2187 | 0.3423          | 0.8958   |
| 0.0419        | 8.0    | 2500 | 0.5879          | 0.8770   |
| 0.0469        | 8.9984 | 2812 | 0.5126          | 0.8854   |
| 0.0302        | 9.984  | 3120 | 0.6068          | 0.8808   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1