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# hushem_1x_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: 1.3101
- Accuracy: 0.6222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.3638          | 0.3556   |
| 1.331         | 2.0   | 12   | 1.3133          | 0.4222   |
| 1.331         | 3.0   | 18   | 1.2851          | 0.4222   |
| 1.0997        | 4.0   | 24   | 1.2715          | 0.4      |
| 0.9418        | 5.0   | 30   | 1.2498          | 0.4444   |
| 0.9418        | 6.0   | 36   | 1.2371          | 0.5111   |
| 0.7701        | 7.0   | 42   | 1.2279          | 0.5111   |
| 0.7701        | 8.0   | 48   | 1.2223          | 0.5556   |
| 0.6624        | 9.0   | 54   | 1.2136          | 0.5333   |
| 0.5468        | 10.0  | 60   | 1.2047          | 0.5111   |
| 0.5468        | 11.0  | 66   | 1.2129          | 0.5333   |
| 0.4638        | 12.0  | 72   | 1.2131          | 0.5556   |
| 0.4638        | 13.0  | 78   | 1.2055          | 0.5778   |
| 0.375         | 14.0  | 84   | 1.2059          | 0.5778   |
| 0.3096        | 15.0  | 90   | 1.2025          | 0.5778   |
| 0.3096        | 16.0  | 96   | 1.2062          | 0.5778   |
| 0.2535        | 17.0  | 102  | 1.2103          | 0.6      |
| 0.2535        | 18.0  | 108  | 1.2313          | 0.5778   |
| 0.2168        | 19.0  | 114  | 1.2293          | 0.5778   |
| 0.1735        | 20.0  | 120  | 1.2169          | 0.6222   |
| 0.1735        | 21.0  | 126  | 1.2306          | 0.6222   |
| 0.1492        | 22.0  | 132  | 1.2370          | 0.6222   |
| 0.1492        | 23.0  | 138  | 1.2467          | 0.6222   |
| 0.1264        | 24.0  | 144  | 1.2411          | 0.6222   |
| 0.1012        | 25.0  | 150  | 1.2438          | 0.6222   |
| 0.1012        | 26.0  | 156  | 1.2523          | 0.6222   |
| 0.0887        | 27.0  | 162  | 1.2537          | 0.6      |
| 0.0887        | 28.0  | 168  | 1.2661          | 0.6222   |
| 0.0734        | 29.0  | 174  | 1.2715          | 0.6222   |
| 0.0647        | 30.0  | 180  | 1.2745          | 0.6      |
| 0.0647        | 31.0  | 186  | 1.2817          | 0.6222   |
| 0.0577        | 32.0  | 192  | 1.2861          | 0.6222   |
| 0.0577        | 33.0  | 198  | 1.2908          | 0.6222   |
| 0.0525        | 34.0  | 204  | 1.2935          | 0.6222   |
| 0.048         | 35.0  | 210  | 1.2969          | 0.6222   |
| 0.048         | 36.0  | 216  | 1.2990          | 0.6      |
| 0.0443        | 37.0  | 222  | 1.3015          | 0.6      |
| 0.0443        | 38.0  | 228  | 1.3052          | 0.6222   |
| 0.0404        | 39.0  | 234  | 1.3082          | 0.6222   |
| 0.0394        | 40.0  | 240  | 1.3089          | 0.6222   |
| 0.0394        | 41.0  | 246  | 1.3101          | 0.6222   |
| 0.0387        | 42.0  | 252  | 1.3101          | 0.6222   |
| 0.0387        | 43.0  | 258  | 1.3101          | 0.6222   |
| 0.0369        | 44.0  | 264  | 1.3101          | 0.6222   |
| 0.0381        | 45.0  | 270  | 1.3101          | 0.6222   |
| 0.0381        | 46.0  | 276  | 1.3101          | 0.6222   |
| 0.0382        | 47.0  | 282  | 1.3101          | 0.6222   |
| 0.0382        | 48.0  | 288  | 1.3101          | 0.6222   |
| 0.037         | 49.0  | 294  | 1.3101          | 0.6222   |
| 0.0386        | 50.0  | 300  | 1.3101          | 0.6222   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

01_normal 02_tapered 03_pyriform 04_amorphous