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# hushem_40x_deit_tiny_rms_001_fold1

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: 7.3853
- Accuracy: 0.5556

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1884        | 1.0   | 215   | 1.1880          | 0.4444   |
| 0.7323        | 2.0   | 430   | 1.1545          | 0.5111   |
| 0.6559        | 3.0   | 645   | 3.0305          | 0.3556   |
| 0.5702        | 4.0   | 860   | 1.2302          | 0.5111   |
| 0.5375        | 5.0   | 1075  | 2.2528          | 0.4222   |
| 0.4472        | 6.0   | 1290  | 1.9208          | 0.5111   |
| 0.4382        | 7.0   | 1505  | 1.8095          | 0.4889   |
| 0.3809        | 8.0   | 1720  | 2.0821          | 0.4222   |
| 0.3012        | 9.0   | 1935  | 1.8136          | 0.4      |
| 0.2478        | 10.0  | 2150  | 2.1397          | 0.4889   |
| 0.2029        | 11.0  | 2365  | 1.9762          | 0.5556   |
| 0.1971        | 12.0  | 2580  | 2.3756          | 0.5778   |
| 0.213         | 13.0  | 2795  | 1.6329          | 0.6444   |
| 0.1476        | 14.0  | 3010  | 2.7699          | 0.5333   |
| 0.098         | 15.0  | 3225  | 2.9763          | 0.5556   |
| 0.1482        | 16.0  | 3440  | 3.4825          | 0.5111   |
| 0.1197        | 17.0  | 3655  | 2.4388          | 0.6444   |
| 0.0935        | 18.0  | 3870  | 2.6931          | 0.5778   |
| 0.0698        | 19.0  | 4085  | 3.8147          | 0.5333   |
| 0.1713        | 20.0  | 4300  | 3.1091          | 0.5556   |
| 0.0331        | 21.0  | 4515  | 3.7485          | 0.5778   |
| 0.0687        | 22.0  | 4730  | 3.9845          | 0.5778   |
| 0.0351        | 23.0  | 4945  | 3.2773          | 0.6      |
| 0.0341        | 24.0  | 5160  | 4.2021          | 0.5333   |
| 0.0324        | 25.0  | 5375  | 6.0388          | 0.4889   |
| 0.022         | 26.0  | 5590  | 4.1761          | 0.6      |
| 0.1048        | 27.0  | 5805  | 2.9470          | 0.6      |
| 0.0202        | 28.0  | 6020  | 3.8209          | 0.5778   |
| 0.0085        | 29.0  | 6235  | 4.1758          | 0.5111   |
| 0.0013        | 30.0  | 6450  | 4.2128          | 0.5556   |
| 0.0026        | 31.0  | 6665  | 4.4304          | 0.4667   |
| 0.0003        | 32.0  | 6880  | 4.6210          | 0.5111   |
| 0.015         | 33.0  | 7095  | 3.7643          | 0.5556   |
| 0.0066        | 34.0  | 7310  | 4.8748          | 0.5778   |
| 0.0           | 35.0  | 7525  | 4.7438          | 0.5556   |
| 0.0           | 36.0  | 7740  | 5.0565          | 0.5111   |
| 0.0           | 37.0  | 7955  | 5.3178          | 0.5333   |
| 0.0           | 38.0  | 8170  | 5.6008          | 0.5333   |
| 0.0           | 39.0  | 8385  | 5.8863          | 0.5333   |
| 0.0           | 40.0  | 8600  | 6.1779          | 0.5333   |
| 0.0           | 41.0  | 8815  | 6.4282          | 0.5333   |
| 0.0           | 42.0  | 9030  | 6.6702          | 0.5556   |
| 0.0           | 43.0  | 9245  | 6.8800          | 0.5556   |
| 0.0           | 44.0  | 9460  | 7.0514          | 0.5556   |
| 0.0           | 45.0  | 9675  | 7.1938          | 0.5556   |
| 0.0           | 46.0  | 9890  | 7.2836          | 0.5556   |
| 0.0           | 47.0  | 10105 | 7.3402          | 0.5556   |
| 0.0           | 48.0  | 10320 | 7.3740          | 0.5556   |
| 0.0           | 49.0  | 10535 | 7.3831          | 0.5556   |
| 0.0           | 50.0  | 10750 | 7.3853          | 0.5556   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "hushem_40x_deit_tiny_rms_001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5555555555555556, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us