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# hushem_40x_deit_tiny_rms_0001_fold2

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: 4.3313
- Accuracy: 0.6667

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1374        | 1.0   | 215   | 1.3718          | 0.7111   |
| 0.0248        | 2.0   | 430   | 1.5033          | 0.7778   |
| 0.0726        | 3.0   | 645   | 1.7295          | 0.7556   |
| 0.0372        | 4.0   | 860   | 1.5869          | 0.7778   |
| 0.0411        | 5.0   | 1075  | 1.1809          | 0.7778   |
| 0.0235        | 6.0   | 1290  | 2.1699          | 0.6889   |
| 0.0004        | 7.0   | 1505  | 1.8564          | 0.7333   |
| 0.0351        | 8.0   | 1720  | 2.6913          | 0.5556   |
| 0.0436        | 9.0   | 1935  | 1.7899          | 0.6889   |
| 0.0311        | 10.0  | 2150  | 2.2763          | 0.7333   |
| 0.0318        | 11.0  | 2365  | 2.1440          | 0.7111   |
| 0.0601        | 12.0  | 2580  | 1.3738          | 0.8      |
| 0.0036        | 13.0  | 2795  | 1.9492          | 0.7556   |
| 0.0024        | 14.0  | 3010  | 2.0010          | 0.7778   |
| 0.0119        | 15.0  | 3225  | 2.9477          | 0.7111   |
| 0.0001        | 16.0  | 3440  | 2.0050          | 0.8222   |
| 0.0           | 17.0  | 3655  | 2.2043          | 0.7778   |
| 0.0045        | 18.0  | 3870  | 2.9253          | 0.6889   |
| 0.0002        | 19.0  | 4085  | 2.4235          | 0.7333   |
| 0.0           | 20.0  | 4300  | 3.4852          | 0.6      |
| 0.0276        | 21.0  | 4515  | 3.0762          | 0.6667   |
| 0.0098        | 22.0  | 4730  | 3.3340          | 0.6222   |
| 0.0328        | 23.0  | 4945  | 1.8687          | 0.8      |
| 0.0           | 24.0  | 5160  | 1.6806          | 0.8      |
| 0.0           | 25.0  | 5375  | 2.3408          | 0.7333   |
| 0.0208        | 26.0  | 5590  | 2.3251          | 0.7778   |
| 0.0           | 27.0  | 5805  | 2.8347          | 0.7111   |
| 0.0           | 28.0  | 6020  | 2.2742          | 0.7333   |
| 0.0           | 29.0  | 6235  | 2.4267          | 0.7111   |
| 0.0           | 30.0  | 6450  | 2.5951          | 0.7111   |
| 0.0           | 31.0  | 6665  | 2.7772          | 0.6889   |
| 0.0           | 32.0  | 6880  | 2.9769          | 0.6889   |
| 0.0           | 33.0  | 7095  | 3.1694          | 0.6889   |
| 0.0           | 34.0  | 7310  | 3.3770          | 0.6889   |
| 0.0           | 35.0  | 7525  | 3.5369          | 0.6889   |
| 0.0           | 36.0  | 7740  | 3.6892          | 0.7111   |
| 0.0           | 37.0  | 7955  | 3.8241          | 0.6889   |
| 0.0           | 38.0  | 8170  | 3.9473          | 0.6889   |
| 0.0           | 39.0  | 8385  | 4.0424          | 0.6889   |
| 0.0           | 40.0  | 8600  | 4.1157          | 0.6889   |
| 0.0           | 41.0  | 8815  | 4.1738          | 0.6667   |
| 0.0           | 42.0  | 9030  | 4.2155          | 0.6667   |
| 0.0           | 43.0  | 9245  | 4.2470          | 0.6667   |
| 0.0           | 44.0  | 9460  | 4.2729          | 0.6667   |
| 0.0           | 45.0  | 9675  | 4.2929          | 0.6667   |
| 0.0           | 46.0  | 9890  | 4.3080          | 0.6667   |
| 0.0           | 47.0  | 10105 | 4.3190          | 0.6667   |
| 0.0           | 48.0  | 10320 | 4.3263          | 0.6667   |
| 0.0           | 49.0  | 10535 | 4.3304          | 0.6667   |
| 0.0           | 50.0  | 10750 | 4.3313          | 0.6667   |


### 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