
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_5x_deit_tiny_adamax_00001_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: 1.6641
- Accuracy: 0.5778

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3635        | 1.0   | 27   | 1.4130          | 0.2667   |
| 1.0042        | 2.0   | 54   | 1.4711          | 0.2222   |
| 0.8161        | 3.0   | 81   | 1.3782          | 0.2667   |
| 0.718         | 4.0   | 108  | 1.4066          | 0.3778   |
| 0.5558        | 5.0   | 135  | 1.3265          | 0.4444   |
| 0.4509        | 6.0   | 162  | 1.2556          | 0.5111   |
| 0.3768        | 7.0   | 189  | 1.2546          | 0.5333   |
| 0.3011        | 8.0   | 216  | 1.2575          | 0.5333   |
| 0.2105        | 9.0   | 243  | 1.2766          | 0.5111   |
| 0.1649        | 10.0  | 270  | 1.2667          | 0.5333   |
| 0.1073        | 11.0  | 297  | 1.2756          | 0.5333   |
| 0.09          | 12.0  | 324  | 1.2325          | 0.5333   |
| 0.0621        | 13.0  | 351  | 1.3118          | 0.5111   |
| 0.0505        | 14.0  | 378  | 1.2588          | 0.5111   |
| 0.0376        | 15.0  | 405  | 1.2895          | 0.5111   |
| 0.0263        | 16.0  | 432  | 1.3784          | 0.5333   |
| 0.0213        | 17.0  | 459  | 1.3797          | 0.5556   |
| 0.0147        | 18.0  | 486  | 1.3696          | 0.5556   |
| 0.0099        | 19.0  | 513  | 1.4119          | 0.5778   |
| 0.0067        | 20.0  | 540  | 1.4307          | 0.5333   |
| 0.0051        | 21.0  | 567  | 1.4626          | 0.5556   |
| 0.0036        | 22.0  | 594  | 1.4677          | 0.5778   |
| 0.0029        | 23.0  | 621  | 1.5080          | 0.5778   |
| 0.0025        | 24.0  | 648  | 1.5082          | 0.5778   |
| 0.002         | 25.0  | 675  | 1.5166          | 0.5556   |
| 0.0019        | 26.0  | 702  | 1.5536          | 0.5556   |
| 0.0018        | 27.0  | 729  | 1.5513          | 0.5556   |
| 0.0016        | 28.0  | 756  | 1.5675          | 0.5556   |
| 0.0015        | 29.0  | 783  | 1.5750          | 0.5778   |
| 0.0014        | 30.0  | 810  | 1.5873          | 0.5778   |
| 0.0012        | 31.0  | 837  | 1.5953          | 0.6      |
| 0.0013        | 32.0  | 864  | 1.6002          | 0.6      |
| 0.001         | 33.0  | 891  | 1.6127          | 0.6      |
| 0.0011        | 34.0  | 918  | 1.6173          | 0.6      |
| 0.0009        | 35.0  | 945  | 1.6219          | 0.5778   |
| 0.001         | 36.0  | 972  | 1.6280          | 0.6      |
| 0.0009        | 37.0  | 999  | 1.6357          | 0.6      |
| 0.0009        | 38.0  | 1026 | 1.6422          | 0.6      |
| 0.0009        | 39.0  | 1053 | 1.6437          | 0.6      |
| 0.0008        | 40.0  | 1080 | 1.6487          | 0.6      |
| 0.0008        | 41.0  | 1107 | 1.6556          | 0.5778   |
| 0.0007        | 42.0  | 1134 | 1.6560          | 0.6      |
| 0.0008        | 43.0  | 1161 | 1.6560          | 0.6      |
| 0.0007        | 44.0  | 1188 | 1.6595          | 0.6      |
| 0.0007        | 45.0  | 1215 | 1.6630          | 0.5778   |
| 0.0007        | 46.0  | 1242 | 1.6626          | 0.6      |
| 0.0007        | 47.0  | 1269 | 1.6639          | 0.5778   |
| 0.0008        | 48.0  | 1296 | 1.6641          | 0.5778   |
| 0.0008        | 49.0  | 1323 | 1.6641          | 0.5778   |
| 0.0007        | 50.0  | 1350 | 1.6641          | 0.5778   |


### 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