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# hushem_5x_deit_small_adamax_00001_fold2

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4402
- Accuracy: 0.6889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2515        | 1.0   | 27   | 1.2615          | 0.5333   |
| 0.9391        | 2.0   | 54   | 1.2122          | 0.5556   |
| 0.6766        | 3.0   | 81   | 1.1537          | 0.5333   |
| 0.5382        | 4.0   | 108  | 1.1591          | 0.6      |
| 0.3747        | 5.0   | 135  | 1.0974          | 0.6444   |
| 0.2681        | 6.0   | 162  | 1.0815          | 0.6444   |
| 0.1892        | 7.0   | 189  | 1.1005          | 0.6222   |
| 0.1214        | 8.0   | 216  | 1.0974          | 0.6222   |
| 0.0863        | 9.0   | 243  | 1.0922          | 0.6444   |
| 0.0475        | 10.0  | 270  | 1.1018          | 0.6667   |
| 0.0299        | 11.0  | 297  | 1.1054          | 0.6889   |
| 0.0156        | 12.0  | 324  | 1.1555          | 0.6667   |
| 0.0095        | 13.0  | 351  | 1.1847          | 0.6667   |
| 0.0067        | 14.0  | 378  | 1.2033          | 0.6667   |
| 0.0051        | 15.0  | 405  | 1.2483          | 0.6667   |
| 0.004         | 16.0  | 432  | 1.2613          | 0.6667   |
| 0.0032        | 17.0  | 459  | 1.2726          | 0.6667   |
| 0.0028        | 18.0  | 486  | 1.2843          | 0.6667   |
| 0.0026        | 19.0  | 513  | 1.2998          | 0.6667   |
| 0.0021        | 20.0  | 540  | 1.3093          | 0.6667   |
| 0.0019        | 21.0  | 567  | 1.3233          | 0.6667   |
| 0.0018        | 22.0  | 594  | 1.3315          | 0.6667   |
| 0.0015        | 23.0  | 621  | 1.3379          | 0.6667   |
| 0.0014        | 24.0  | 648  | 1.3489          | 0.6667   |
| 0.0014        | 25.0  | 675  | 1.3547          | 0.6667   |
| 0.0013        | 26.0  | 702  | 1.3608          | 0.6889   |
| 0.0012        | 27.0  | 729  | 1.3706          | 0.6667   |
| 0.0011        | 28.0  | 756  | 1.3780          | 0.6667   |
| 0.0012        | 29.0  | 783  | 1.3808          | 0.6889   |
| 0.0011        | 30.0  | 810  | 1.3868          | 0.6889   |
| 0.001         | 31.0  | 837  | 1.3922          | 0.6889   |
| 0.001         | 32.0  | 864  | 1.3991          | 0.6889   |
| 0.0009        | 33.0  | 891  | 1.4019          | 0.6889   |
| 0.0009        | 34.0  | 918  | 1.4078          | 0.6889   |
| 0.0009        | 35.0  | 945  | 1.4120          | 0.6889   |
| 0.0008        | 36.0  | 972  | 1.4161          | 0.6889   |
| 0.0008        | 37.0  | 999  | 1.4179          | 0.6889   |
| 0.0008        | 38.0  | 1026 | 1.4222          | 0.6889   |
| 0.0007        | 39.0  | 1053 | 1.4264          | 0.6889   |
| 0.0007        | 40.0  | 1080 | 1.4282          | 0.6889   |
| 0.0007        | 41.0  | 1107 | 1.4320          | 0.6889   |
| 0.0007        | 42.0  | 1134 | 1.4342          | 0.6889   |
| 0.0007        | 43.0  | 1161 | 1.4365          | 0.6889   |
| 0.0007        | 44.0  | 1188 | 1.4366          | 0.6889   |
| 0.0007        | 45.0  | 1215 | 1.4383          | 0.6889   |
| 0.0007        | 46.0  | 1242 | 1.4394          | 0.6889   |
| 0.0007        | 47.0  | 1269 | 1.4399          | 0.6889   |
| 0.0007        | 48.0  | 1296 | 1.4402          | 0.6889   |
| 0.0007        | 49.0  | 1323 | 1.4402          | 0.6889   |
| 0.0007        | 50.0  | 1350 | 1.4402          | 0.6889   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

01_normal 02_tapered 03_pyriform 04_amorphous