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# hushem_40x_deit_small_rms_001_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: 7.1718
- Accuracy: 0.6

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2965        | 1.0   | 215   | 1.2091          | 0.4667   |
| 0.8177        | 2.0   | 430   | 1.2899          | 0.5333   |
| 0.7013        | 3.0   | 645   | 1.2461          | 0.5111   |
| 0.6618        | 4.0   | 860   | 1.7839          | 0.4444   |
| 0.462         | 5.0   | 1075  | 1.6189          | 0.4889   |
| 0.4201        | 6.0   | 1290  | 2.6718          | 0.4889   |
| 0.3471        | 7.0   | 1505  | 2.6469          | 0.5556   |
| 0.3247        | 8.0   | 1720  | 2.5316          | 0.5778   |
| 0.3947        | 9.0   | 1935  | 2.1794          | 0.5556   |
| 0.3688        | 10.0  | 2150  | 2.4409          | 0.4889   |
| 0.3554        | 11.0  | 2365  | 2.7892          | 0.5556   |
| 0.3048        | 12.0  | 2580  | 3.7146          | 0.5333   |
| 0.3088        | 13.0  | 2795  | 2.9395          | 0.6      |
| 0.2595        | 14.0  | 3010  | 2.6649          | 0.6222   |
| 0.2467        | 15.0  | 3225  | 3.0874          | 0.5778   |
| 0.2539        | 16.0  | 3440  | 3.4419          | 0.6      |
| 0.2637        | 17.0  | 3655  | 3.2496          | 0.6      |
| 0.2157        | 18.0  | 3870  | 3.3961          | 0.6      |
| 0.1038        | 19.0  | 4085  | 4.4011          | 0.6      |
| 0.1844        | 20.0  | 4300  | 3.9340          | 0.5111   |
| 0.1977        | 21.0  | 4515  | 4.0238          | 0.5556   |
| 0.1597        | 22.0  | 4730  | 3.8533          | 0.5778   |
| 0.1177        | 23.0  | 4945  | 4.1555          | 0.5556   |
| 0.0976        | 24.0  | 5160  | 3.8653          | 0.6222   |
| 0.106         | 25.0  | 5375  | 3.5209          | 0.5778   |
| 0.0483        | 26.0  | 5590  | 4.5365          | 0.6222   |
| 0.0977        | 27.0  | 5805  | 3.6449          | 0.6      |
| 0.115         | 28.0  | 6020  | 4.3353          | 0.6      |
| 0.0948        | 29.0  | 6235  | 4.1300          | 0.6222   |
| 0.0615        | 30.0  | 6450  | 4.7232          | 0.6      |
| 0.1033        | 31.0  | 6665  | 4.3508          | 0.5778   |
| 0.0812        | 32.0  | 6880  | 4.5803          | 0.5778   |
| 0.056         | 33.0  | 7095  | 4.4372          | 0.6222   |
| 0.0361        | 34.0  | 7310  | 4.9845          | 0.6444   |
| 0.0141        | 35.0  | 7525  | 6.0367          | 0.5778   |
| 0.0009        | 36.0  | 7740  | 5.8383          | 0.6222   |
| 0.0009        | 37.0  | 7955  | 5.7637          | 0.6222   |
| 0.0203        | 38.0  | 8170  | 5.3901          | 0.6      |
| 0.049         | 39.0  | 8385  | 5.5891          | 0.5778   |
| 0.0029        | 40.0  | 8600  | 5.9302          | 0.5778   |
| 0.0002        | 41.0  | 8815  | 5.9565          | 0.5778   |
| 0.0046        | 42.0  | 9030  | 6.4259          | 0.5778   |
| 0.0003        | 43.0  | 9245  | 6.2149          | 0.6222   |
| 0.0           | 44.0  | 9460  | 6.6058          | 0.6      |
| 0.0           | 45.0  | 9675  | 6.5823          | 0.6      |
| 0.0           | 46.0  | 9890  | 6.7170          | 0.6      |
| 0.0           | 47.0  | 10105 | 6.8829          | 0.6      |
| 0.0           | 48.0  | 10320 | 7.0021          | 0.6      |
| 0.0           | 49.0  | 10535 | 7.1301          | 0.6      |
| 0.0           | 50.0  | 10750 | 7.1718          | 0.6      |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+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-small-patch16-224", "model-index": [{"name": "hushem_40x_deit_small_rms_001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6, "name": "Accuracy"}]}]}]}
transformers pytorch 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