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# smids_3x_deit_base_sgd_001_fold3

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: 0.2808
- Accuracy: 0.8867

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.957         | 1.0   | 225   | 0.9484          | 0.6067   |
| 0.7319        | 2.0   | 450   | 0.7399          | 0.7417   |
| 0.5675        | 3.0   | 675   | 0.6023          | 0.8      |
| 0.5071        | 4.0   | 900   | 0.5170          | 0.8183   |
| 0.4486        | 5.0   | 1125  | 0.4641          | 0.8317   |
| 0.3985        | 6.0   | 1350  | 0.4275          | 0.85     |
| 0.3723        | 7.0   | 1575  | 0.4010          | 0.8483   |
| 0.3723        | 8.0   | 1800  | 0.3821          | 0.8533   |
| 0.3669        | 9.0   | 2025  | 0.3688          | 0.8617   |
| 0.3526        | 10.0  | 2250  | 0.3586          | 0.8667   |
| 0.3131        | 11.0  | 2475  | 0.3476          | 0.8733   |
| 0.3182        | 12.0  | 2700  | 0.3438          | 0.8717   |
| 0.329         | 13.0  | 2925  | 0.3317          | 0.875    |
| 0.2936        | 14.0  | 3150  | 0.3264          | 0.8733   |
| 0.281         | 15.0  | 3375  | 0.3211          | 0.875    |
| 0.29          | 16.0  | 3600  | 0.3177          | 0.875    |
| 0.3306        | 17.0  | 3825  | 0.3133          | 0.8767   |
| 0.268         | 18.0  | 4050  | 0.3109          | 0.875    |
| 0.2813        | 19.0  | 4275  | 0.3073          | 0.8817   |
| 0.29          | 20.0  | 4500  | 0.3041          | 0.8833   |
| 0.2543        | 21.0  | 4725  | 0.3034          | 0.8833   |
| 0.2485        | 22.0  | 4950  | 0.3036          | 0.8833   |
| 0.2389        | 23.0  | 5175  | 0.2976          | 0.885    |
| 0.2585        | 24.0  | 5400  | 0.2973          | 0.885    |
| 0.2265        | 25.0  | 5625  | 0.2954          | 0.8867   |
| 0.2806        | 26.0  | 5850  | 0.2939          | 0.8867   |
| 0.2023        | 27.0  | 6075  | 0.2926          | 0.8867   |
| 0.2462        | 28.0  | 6300  | 0.2897          | 0.885    |
| 0.2516        | 29.0  | 6525  | 0.2898          | 0.8867   |
| 0.2125        | 30.0  | 6750  | 0.2889          | 0.8867   |
| 0.2359        | 31.0  | 6975  | 0.2881          | 0.8883   |
| 0.2277        | 32.0  | 7200  | 0.2865          | 0.8867   |
| 0.2555        | 33.0  | 7425  | 0.2855          | 0.8883   |
| 0.202         | 34.0  | 7650  | 0.2847          | 0.8883   |
| 0.2329        | 35.0  | 7875  | 0.2859          | 0.8883   |
| 0.262         | 36.0  | 8100  | 0.2851          | 0.8883   |
| 0.2072        | 37.0  | 8325  | 0.2831          | 0.8867   |
| 0.2187        | 38.0  | 8550  | 0.2836          | 0.8867   |
| 0.2311        | 39.0  | 8775  | 0.2822          | 0.8867   |
| 0.2221        | 40.0  | 9000  | 0.2824          | 0.8867   |
| 0.2051        | 41.0  | 9225  | 0.2822          | 0.8867   |
| 0.2267        | 42.0  | 9450  | 0.2815          | 0.8867   |
| 0.2187        | 43.0  | 9675  | 0.2815          | 0.8867   |
| 0.2138        | 44.0  | 9900  | 0.2815          | 0.8867   |
| 0.2129        | 45.0  | 10125 | 0.2813          | 0.8867   |
| 0.2034        | 46.0  | 10350 | 0.2810          | 0.8867   |
| 0.2287        | 47.0  | 10575 | 0.2808          | 0.8867   |
| 0.2051        | 48.0  | 10800 | 0.2807          | 0.8867   |
| 0.256         | 49.0  | 11025 | 0.2807          | 0.8867   |
| 0.2173        | 50.0  | 11250 | 0.2808          | 0.8867   |


### 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-base-patch16-224", "model-index": [{"name": "smids_3x_deit_base_sgd_001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8866666666666667, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us