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# hushem_40x_deit_tiny_adamax_00001_fold1

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7285
- Accuracy: 0.7778

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3612        | 1.0   | 215   | 0.8053          | 0.7111   |
| 0.0954        | 2.0   | 430   | 0.7023          | 0.7111   |
| 0.0263        | 3.0   | 645   | 0.7672          | 0.7333   |
| 0.0113        | 4.0   | 860   | 0.8377          | 0.7778   |
| 0.0012        | 5.0   | 1075  | 0.9748          | 0.7778   |
| 0.0007        | 6.0   | 1290  | 0.9997          | 0.7778   |
| 0.0004        | 7.0   | 1505  | 1.1150          | 0.7556   |
| 0.0003        | 8.0   | 1720  | 1.1439          | 0.7556   |
| 0.0002        | 9.0   | 1935  | 1.2019          | 0.7556   |
| 0.0001        | 10.0  | 2150  | 1.2424          | 0.7556   |
| 0.0001        | 11.0  | 2365  | 1.2284          | 0.7556   |
| 0.0001        | 12.0  | 2580  | 1.2809          | 0.7556   |
| 0.0001        | 13.0  | 2795  | 1.3071          | 0.7556   |
| 0.0001        | 14.0  | 3010  | 1.3721          | 0.7556   |
| 0.0           | 15.0  | 3225  | 1.3804          | 0.7556   |
| 0.0           | 16.0  | 3440  | 1.3850          | 0.7556   |
| 0.0           | 17.0  | 3655  | 1.4005          | 0.7556   |
| 0.0           | 18.0  | 3870  | 1.4317          | 0.7556   |
| 0.0           | 19.0  | 4085  | 1.4823          | 0.7556   |
| 0.0           | 20.0  | 4300  | 1.4810          | 0.7556   |
| 0.0           | 21.0  | 4515  | 1.4751          | 0.7556   |
| 0.0           | 22.0  | 4730  | 1.5073          | 0.7556   |
| 0.0           | 23.0  | 4945  | 1.5283          | 0.7333   |
| 0.0           | 24.0  | 5160  | 1.5592          | 0.7556   |
| 0.0           | 25.0  | 5375  | 1.5298          | 0.7556   |
| 0.0           | 26.0  | 5590  | 1.5228          | 0.7778   |
| 0.0           | 27.0  | 5805  | 1.5617          | 0.7556   |
| 0.0           | 28.0  | 6020  | 1.5609          | 0.7778   |
| 0.0           | 29.0  | 6235  | 1.5791          | 0.7556   |
| 0.0           | 30.0  | 6450  | 1.6043          | 0.7778   |
| 0.0           | 31.0  | 6665  | 1.6159          | 0.7556   |
| 0.0           | 32.0  | 6880  | 1.6584          | 0.7556   |
| 0.0           | 33.0  | 7095  | 1.6250          | 0.7778   |
| 0.0           | 34.0  | 7310  | 1.6097          | 0.7778   |
| 0.0           | 35.0  | 7525  | 1.6615          | 0.7778   |
| 0.0           | 36.0  | 7740  | 1.6489          | 0.7778   |
| 0.0           | 37.0  | 7955  | 1.6559          | 0.7778   |
| 0.0           | 38.0  | 8170  | 1.6854          | 0.7778   |
| 0.0           | 39.0  | 8385  | 1.6826          | 0.7778   |
| 0.0           | 40.0  | 8600  | 1.7344          | 0.7333   |
| 0.0           | 41.0  | 8815  | 1.7007          | 0.7778   |
| 0.0           | 42.0  | 9030  | 1.6800          | 0.7778   |
| 0.0           | 43.0  | 9245  | 1.7149          | 0.7778   |
| 0.0           | 44.0  | 9460  | 1.7189          | 0.7556   |
| 0.0           | 45.0  | 9675  | 1.7288          | 0.7778   |
| 0.0           | 46.0  | 9890  | 1.7097          | 0.7778   |
| 0.0           | 47.0  | 10105 | 1.7285          | 0.7778   |
| 0.0           | 48.0  | 10320 | 1.7184          | 0.7778   |
| 0.0           | 49.0  | 10535 | 1.7322          | 0.7778   |
| 0.0           | 50.0  | 10750 | 1.7285          | 0.7778   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

01_normal 02_tapered 03_pyriform 04_amorphous