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# hushem_1x_deit_small_adamax_00001_fold3

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: 0.6553
- Accuracy: 0.6512

## 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    | 1.3641          | 0.3953   |
| 1.3358        | 2.0   | 12   | 1.2934          | 0.4186   |
| 1.3358        | 3.0   | 18   | 1.2307          | 0.4419   |
| 1.1053        | 4.0   | 24   | 1.1728          | 0.5814   |
| 0.9503        | 5.0   | 30   | 1.1200          | 0.5814   |
| 0.9503        | 6.0   | 36   | 1.0691          | 0.5814   |
| 0.8249        | 7.0   | 42   | 1.0268          | 0.6047   |
| 0.8249        | 8.0   | 48   | 1.0002          | 0.6279   |
| 0.6991        | 9.0   | 54   | 0.9588          | 0.6279   |
| 0.62          | 10.0  | 60   | 0.9254          | 0.6279   |
| 0.62          | 11.0  | 66   | 0.8988          | 0.6744   |
| 0.5003        | 12.0  | 72   | 0.8718          | 0.6279   |
| 0.5003        | 13.0  | 78   | 0.8636          | 0.6279   |
| 0.4251        | 14.0  | 84   | 0.8486          | 0.6279   |
| 0.3584        | 15.0  | 90   | 0.8228          | 0.6279   |
| 0.3584        | 16.0  | 96   | 0.8029          | 0.6512   |
| 0.2955        | 17.0  | 102  | 0.7980          | 0.6279   |
| 0.2955        | 18.0  | 108  | 0.7871          | 0.6047   |
| 0.2345        | 19.0  | 114  | 0.7646          | 0.6279   |
| 0.2022        | 20.0  | 120  | 0.7571          | 0.6279   |
| 0.2022        | 21.0  | 126  | 0.7433          | 0.6512   |
| 0.1667        | 22.0  | 132  | 0.7314          | 0.6744   |
| 0.1667        | 23.0  | 138  | 0.7263          | 0.6279   |
| 0.1461        | 24.0  | 144  | 0.7221          | 0.6744   |
| 0.1251        | 25.0  | 150  | 0.7120          | 0.6512   |
| 0.1251        | 26.0  | 156  | 0.6954          | 0.6512   |
| 0.1033        | 27.0  | 162  | 0.6904          | 0.6512   |
| 0.1033        | 28.0  | 168  | 0.6870          | 0.6744   |
| 0.0941        | 29.0  | 174  | 0.6821          | 0.6744   |
| 0.0792        | 30.0  | 180  | 0.6785          | 0.6744   |
| 0.0792        | 31.0  | 186  | 0.6761          | 0.6744   |
| 0.0681        | 32.0  | 192  | 0.6723          | 0.6744   |
| 0.0681        | 33.0  | 198  | 0.6679          | 0.6744   |
| 0.0621        | 34.0  | 204  | 0.6648          | 0.6512   |
| 0.0554        | 35.0  | 210  | 0.6628          | 0.6512   |
| 0.0554        | 36.0  | 216  | 0.6584          | 0.6744   |
| 0.0533        | 37.0  | 222  | 0.6569          | 0.6744   |
| 0.0533        | 38.0  | 228  | 0.6569          | 0.6512   |
| 0.0487        | 39.0  | 234  | 0.6565          | 0.6512   |
| 0.0478        | 40.0  | 240  | 0.6552          | 0.6512   |
| 0.0478        | 41.0  | 246  | 0.6553          | 0.6512   |
| 0.0459        | 42.0  | 252  | 0.6553          | 0.6512   |
| 0.0459        | 43.0  | 258  | 0.6553          | 0.6512   |
| 0.0488        | 44.0  | 264  | 0.6553          | 0.6512   |
| 0.0454        | 45.0  | 270  | 0.6553          | 0.6512   |
| 0.0454        | 46.0  | 276  | 0.6553          | 0.6512   |
| 0.0445        | 47.0  | 282  | 0.6553          | 0.6512   |
| 0.0445        | 48.0  | 288  | 0.6553          | 0.6512   |
| 0.0487        | 49.0  | 294  | 0.6553          | 0.6512   |
| 0.0463        | 50.0  | 300  | 0.6553          | 0.6512   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-small-patch16-224", "model-index": [{"name": "hushem_1x_deit_small_adamax_00001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6511627906976745, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us