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# swin-tiny-patch4-window7-224-finetuned-leukemia.v2.0

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: 0.5694
- Accuracy: 0.8855

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.4734        | 0.9984  | 312  | 0.7528          | 0.5968   |
| 0.3596        | 2.0     | 625  | 0.8091          | 0.688    |
| 0.2991        | 2.9984  | 937  | 0.9220          | 0.6335   |
| 0.2658        | 4.0     | 1250 | 0.7774          | 0.7137   |
| 0.2511        | 4.9984  | 1562 | 0.4364          | 0.8267   |
| 0.2218        | 6.0     | 1875 | 0.6225          | 0.7837   |
| 0.1691        | 6.9984  | 2187 | 0.3587          | 0.8718   |
| 0.1721        | 8.0     | 2500 | 0.6494          | 0.7987   |
| 0.1393        | 8.9984  | 2812 | 0.6802          | 0.818    |
| 0.1109        | 10.0    | 3125 | 0.5511          | 0.834    |
| 0.1213        | 10.9984 | 3437 | 0.5982          | 0.8417   |
| 0.0971        | 12.0    | 3750 | 0.8005          | 0.814    |
| 0.1121        | 12.9984 | 4062 | 0.6397          | 0.8407   |
| 0.0947        | 14.0    | 4375 | 1.0869          | 0.768    |
| 0.1022        | 14.9984 | 4687 | 0.5969          | 0.8515   |
| 0.0801        | 16.0    | 5000 | 0.5839          | 0.8732   |
| 0.0951        | 16.9984 | 5312 | 0.8599          | 0.827    |
| 0.0716        | 18.0    | 5625 | 0.8355          | 0.822    |
| 0.0859        | 18.9984 | 5937 | 0.7547          | 0.8427   |
| 0.0661        | 20.0    | 6250 | 0.7206          | 0.851    |
| 0.0543        | 20.9984 | 6562 | 0.8396          | 0.8363   |
| 0.0646        | 22.0    | 6875 | 0.5467          | 0.881    |
| 0.0563        | 22.9984 | 7187 | 0.5694          | 0.8855   |
| 0.042         | 24.0    | 7500 | 0.8404          | 0.8492   |
| 0.0638        | 24.9984 | 7812 | 0.9300          | 0.84     |
| 0.0455        | 26.0    | 8125 | 0.9865          | 0.8393   |
| 0.037         | 26.9984 | 8437 | 0.8503          | 0.8525   |
| 0.0469        | 28.0    | 8750 | 0.8272          | 0.8602   |
| 0.0409        | 28.9984 | 9062 | 0.8988          | 0.8502   |
| 0.0438        | 29.9520 | 9360 | 0.8338          | 0.858    |


### Framework versions

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

hem all