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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV35

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2578
- Accuracy: 0.7

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.85          | 1.0     | 36   | 1.4133          | 0.5333   |
| 1.9294        | 2.0     | 72   | 0.9294          | 0.6333   |
| 1.1818        | 3.0     | 108  | 0.7700          | 0.65     |
| 0.7534        | 4.0     | 144  | 0.7531          | 0.7167   |
| 0.4285        | 5.0     | 180  | 0.9580          | 0.7      |
| 0.08          | 6.0     | 216  | 1.1785          | 0.75     |
| 0.0891        | 7.0     | 252  | 1.4686          | 0.7333   |
| 0.0602        | 8.0     | 288  | 1.7816          | 0.7      |
| 0.0284        | 9.0     | 324  | 1.5790          | 0.7667   |
| 0.0513        | 10.0    | 360  | 1.8933          | 0.7      |
| 0.0335        | 11.0    | 396  | 2.1433          | 0.65     |
| 0.025         | 12.0    | 432  | 2.3483          | 0.6667   |
| 0.0246        | 13.0    | 468  | 2.6426          | 0.6667   |
| 0.0306        | 14.0    | 504  | 3.0153          | 0.65     |
| 0.016         | 15.0    | 540  | 3.1259          | 0.6833   |
| 0.006         | 16.0    | 576  | 2.7612          | 0.7167   |
| 0.0234        | 17.0    | 612  | 2.5334          | 0.7167   |
| 0.0025        | 18.0    | 648  | 2.1768          | 0.7667   |
| 0.0001        | 19.0    | 684  | 2.6585          | 0.7167   |
| 0.0007        | 20.0    | 720  | 2.3282          | 0.7167   |
| 0.0003        | 21.0    | 756  | 2.6975          | 0.7333   |
| 0.0003        | 22.0    | 792  | 2.6186          | 0.7      |
| 0.0006        | 23.0    | 828  | 2.9600          | 0.7167   |
| 0.0008        | 24.0    | 864  | 2.9623          | 0.7333   |
| 0.0002        | 25.0    | 900  | 2.8632          | 0.7167   |
| 0.0143        | 26.0    | 936  | 2.8460          | 0.7167   |
| 0.0           | 27.0    | 972  | 2.9372          | 0.7167   |
| 0.0002        | 28.0    | 1008 | 2.8056          | 0.75     |
| 0.0001        | 29.0    | 1044 | 3.0591          | 0.7167   |
| 0.0001        | 30.0    | 1080 | 3.3295          | 0.6833   |
| 0.0           | 31.0    | 1116 | 3.2851          | 0.6833   |
| 0.0001        | 32.0    | 1152 | 3.4065          | 0.7      |
| 0.0           | 33.0    | 1188 | 3.3669          | 0.7      |
| 0.0           | 34.0    | 1224 | 3.3185          | 0.7167   |
| 0.0006        | 35.0    | 1260 | 3.2563          | 0.7      |
| 0.0004        | 36.0    | 1296 | 3.2831          | 0.7      |
| 0.0001        | 37.0    | 1332 | 3.2594          | 0.7      |
| 0.0           | 38.0    | 1368 | 3.2576          | 0.7      |
| 0.0           | 38.9014 | 1400 | 3.2578          | 0.7      |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0

label_0 label_1 label_2 label_3 label_4