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# hushem_40x_deit_tiny_adamax_001_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: 2.2299
- Accuracy: 0.7333

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2388        | 1.0   | 215   | 1.5575          | 0.6444   |
| 0.1132        | 2.0   | 430   | 1.5074          | 0.7111   |
| 0.0448        | 3.0   | 645   | 1.5221          | 0.7111   |
| 0.0294        | 4.0   | 860   | 2.1715          | 0.6444   |
| 0.0359        | 5.0   | 1075  | 2.5882          | 0.6667   |
| 0.041         | 6.0   | 1290  | 3.4111          | 0.6667   |
| 0.0762        | 7.0   | 1505  | 2.4705          | 0.6444   |
| 0.014         | 8.0   | 1720  | 2.7547          | 0.6222   |
| 0.0243        | 9.0   | 1935  | 2.3966          | 0.6889   |
| 0.0008        | 10.0  | 2150  | 2.0479          | 0.6889   |
| 0.0216        | 11.0  | 2365  | 2.7964          | 0.6889   |
| 0.0033        | 12.0  | 2580  | 1.0097          | 0.8      |
| 0.0068        | 13.0  | 2795  | 2.2109          | 0.7556   |
| 0.0003        | 14.0  | 3010  | 2.4149          | 0.6889   |
| 0.0104        | 15.0  | 3225  | 2.3252          | 0.6889   |
| 0.0005        | 16.0  | 3440  | 1.9451          | 0.8      |
| 0.0158        | 17.0  | 3655  | 2.3698          | 0.7333   |
| 0.0           | 18.0  | 3870  | 2.5005          | 0.6889   |
| 0.0001        | 19.0  | 4085  | 2.8562          | 0.7333   |
| 0.0002        | 20.0  | 4300  | 2.0511          | 0.7778   |
| 0.0           | 21.0  | 4515  | 2.4064          | 0.6889   |
| 0.0           | 22.0  | 4730  | 2.3086          | 0.7111   |
| 0.0           | 23.0  | 4945  | 2.2846          | 0.7111   |
| 0.0           | 24.0  | 5160  | 2.2636          | 0.7111   |
| 0.0           | 25.0  | 5375  | 2.2498          | 0.7111   |
| 0.0           | 26.0  | 5590  | 2.2376          | 0.7111   |
| 0.0           | 27.0  | 5805  | 2.2259          | 0.7111   |
| 0.0           | 28.0  | 6020  | 2.2168          | 0.7111   |
| 0.0           | 29.0  | 6235  | 2.2093          | 0.7111   |
| 0.0           | 30.0  | 6450  | 2.2030          | 0.7111   |
| 0.0           | 31.0  | 6665  | 2.1968          | 0.7111   |
| 0.0           | 32.0  | 6880  | 2.1940          | 0.7111   |
| 0.0           | 33.0  | 7095  | 2.1890          | 0.7111   |
| 0.0           | 34.0  | 7310  | 2.1860          | 0.7111   |
| 0.0           | 35.0  | 7525  | 2.1850          | 0.7111   |
| 0.0           | 36.0  | 7740  | 2.1848          | 0.7333   |
| 0.0           | 37.0  | 7955  | 2.1855          | 0.7333   |
| 0.0           | 38.0  | 8170  | 2.1862          | 0.7333   |
| 0.0           | 39.0  | 8385  | 2.1884          | 0.7333   |
| 0.0           | 40.0  | 8600  | 2.1906          | 0.7333   |
| 0.0           | 41.0  | 8815  | 2.1950          | 0.7333   |
| 0.0           | 42.0  | 9030  | 2.1985          | 0.7333   |
| 0.0           | 43.0  | 9245  | 2.2034          | 0.7333   |
| 0.0           | 44.0  | 9460  | 2.2083          | 0.7333   |
| 0.0           | 45.0  | 9675  | 2.2137          | 0.7333   |
| 0.0           | 46.0  | 9890  | 2.2189          | 0.7333   |
| 0.0           | 47.0  | 10105 | 2.2227          | 0.7333   |
| 0.0           | 48.0  | 10320 | 2.2266          | 0.7333   |
| 0.0           | 49.0  | 10535 | 2.2294          | 0.7333   |
| 0.0           | 50.0  | 10750 | 2.2299          | 0.7333   |


### 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