
<!-- 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_base_sgd_00001_fold2

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4730
- Accuracy: 0.1333

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4315        | 1.0   | 27   | 1.4792          | 0.1333   |
| 1.4149        | 2.0   | 54   | 1.4789          | 0.1333   |
| 1.4076        | 3.0   | 81   | 1.4787          | 0.1333   |
| 1.4207        | 4.0   | 108  | 1.4784          | 0.1333   |
| 1.4176        | 5.0   | 135  | 1.4781          | 0.1333   |
| 1.4263        | 6.0   | 162  | 1.4779          | 0.1333   |
| 1.4107        | 7.0   | 189  | 1.4777          | 0.1333   |
| 1.4322        | 8.0   | 216  | 1.4774          | 0.1333   |
| 1.4251        | 9.0   | 243  | 1.4772          | 0.1333   |
| 1.4152        | 10.0  | 270  | 1.4769          | 0.1333   |
| 1.4192        | 11.0  | 297  | 1.4767          | 0.1333   |
| 1.3919        | 12.0  | 324  | 1.4765          | 0.1333   |
| 1.43          | 13.0  | 351  | 1.4763          | 0.1333   |
| 1.414         | 14.0  | 378  | 1.4761          | 0.1333   |
| 1.4238        | 15.0  | 405  | 1.4759          | 0.1333   |
| 1.4169        | 16.0  | 432  | 1.4757          | 0.1333   |
| 1.4177        | 17.0  | 459  | 1.4756          | 0.1333   |
| 1.4175        | 18.0  | 486  | 1.4754          | 0.1333   |
| 1.4184        | 19.0  | 513  | 1.4752          | 0.1333   |
| 1.4223        | 20.0  | 540  | 1.4751          | 0.1333   |
| 1.4089        | 21.0  | 567  | 1.4749          | 0.1333   |
| 1.409         | 22.0  | 594  | 1.4748          | 0.1333   |
| 1.4409        | 23.0  | 621  | 1.4746          | 0.1333   |
| 1.4227        | 24.0  | 648  | 1.4745          | 0.1333   |
| 1.4077        | 25.0  | 675  | 1.4744          | 0.1333   |
| 1.4191        | 26.0  | 702  | 1.4742          | 0.1333   |
| 1.4141        | 27.0  | 729  | 1.4741          | 0.1333   |
| 1.3944        | 28.0  | 756  | 1.4740          | 0.1333   |
| 1.4213        | 29.0  | 783  | 1.4739          | 0.1333   |
| 1.4096        | 30.0  | 810  | 1.4738          | 0.1333   |
| 1.4271        | 31.0  | 837  | 1.4737          | 0.1333   |
| 1.4292        | 32.0  | 864  | 1.4736          | 0.1333   |
| 1.4137        | 33.0  | 891  | 1.4736          | 0.1333   |
| 1.4102        | 34.0  | 918  | 1.4735          | 0.1333   |
| 1.4169        | 35.0  | 945  | 1.4734          | 0.1333   |
| 1.4263        | 36.0  | 972  | 1.4734          | 0.1333   |
| 1.4324        | 37.0  | 999  | 1.4733          | 0.1333   |
| 1.4156        | 38.0  | 1026 | 1.4733          | 0.1333   |
| 1.4286        | 39.0  | 1053 | 1.4732          | 0.1333   |
| 1.41          | 40.0  | 1080 | 1.4732          | 0.1333   |
| 1.411         | 41.0  | 1107 | 1.4731          | 0.1333   |
| 1.4185        | 42.0  | 1134 | 1.4731          | 0.1333   |
| 1.3968        | 43.0  | 1161 | 1.4731          | 0.1333   |
| 1.4281        | 44.0  | 1188 | 1.4731          | 0.1333   |
| 1.4179        | 45.0  | 1215 | 1.4730          | 0.1333   |
| 1.4304        | 46.0  | 1242 | 1.4730          | 0.1333   |
| 1.4248        | 47.0  | 1269 | 1.4730          | 0.1333   |
| 1.4232        | 48.0  | 1296 | 1.4730          | 0.1333   |
| 1.4271        | 49.0  | 1323 | 1.4730          | 0.1333   |
| 1.4279        | 50.0  | 1350 | 1.4730          | 0.1333   |


### 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