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# smids_3x_deit_base_sgd_001_fold1

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: 0.2890
- Accuracy: 0.8881

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0344        | 1.0   | 226   | 1.0573          | 0.3890   |
| 0.8639        | 2.0   | 452   | 0.8826          | 0.6477   |
| 0.7159        | 3.0   | 678   | 0.7365          | 0.7446   |
| 0.6314        | 4.0   | 904   | 0.6382          | 0.7679   |
| 0.597         | 5.0   | 1130  | 0.5681          | 0.7863   |
| 0.5391        | 6.0   | 1356  | 0.5171          | 0.8114   |
| 0.4375        | 7.0   | 1582  | 0.4782          | 0.8197   |
| 0.4581        | 8.0   | 1808  | 0.4491          | 0.8230   |
| 0.4008        | 9.0   | 2034  | 0.4274          | 0.8347   |
| 0.3889        | 10.0  | 2260  | 0.4080          | 0.8397   |
| 0.3787        | 11.0  | 2486  | 0.3914          | 0.8481   |
| 0.3295        | 12.0  | 2712  | 0.3805          | 0.8531   |
| 0.2853        | 13.0  | 2938  | 0.3695          | 0.8564   |
| 0.2978        | 14.0  | 3164  | 0.3604          | 0.8614   |
| 0.3683        | 15.0  | 3390  | 0.3519          | 0.8631   |
| 0.3241        | 16.0  | 3616  | 0.3458          | 0.8681   |
| 0.2768        | 17.0  | 3842  | 0.3403          | 0.8664   |
| 0.2702        | 18.0  | 4068  | 0.3347          | 0.8715   |
| 0.3185        | 19.0  | 4294  | 0.3297          | 0.8698   |
| 0.2447        | 20.0  | 4520  | 0.3262          | 0.8748   |
| 0.2875        | 21.0  | 4746  | 0.3219          | 0.8731   |
| 0.306         | 22.0  | 4972  | 0.3191          | 0.8765   |
| 0.3078        | 23.0  | 5198  | 0.3168          | 0.8765   |
| 0.3159        | 24.0  | 5424  | 0.3134          | 0.8781   |
| 0.2262        | 25.0  | 5650  | 0.3107          | 0.8815   |
| 0.3153        | 26.0  | 5876  | 0.3083          | 0.8815   |
| 0.237         | 27.0  | 6102  | 0.3073          | 0.8831   |
| 0.2672        | 28.0  | 6328  | 0.3044          | 0.8815   |
| 0.1997        | 29.0  | 6554  | 0.3037          | 0.8815   |
| 0.3208        | 30.0  | 6780  | 0.3027          | 0.8831   |
| 0.2656        | 31.0  | 7006  | 0.3004          | 0.8848   |
| 0.2803        | 32.0  | 7232  | 0.2988          | 0.8865   |
| 0.1992        | 33.0  | 7458  | 0.2984          | 0.8848   |
| 0.2153        | 34.0  | 7684  | 0.2965          | 0.8865   |
| 0.2588        | 35.0  | 7910  | 0.2955          | 0.8848   |
| 0.2121        | 36.0  | 8136  | 0.2953          | 0.8848   |
| 0.2496        | 37.0  | 8362  | 0.2940          | 0.8881   |
| 0.2614        | 38.0  | 8588  | 0.2931          | 0.8865   |
| 0.2271        | 39.0  | 8814  | 0.2926          | 0.8865   |
| 0.1865        | 40.0  | 9040  | 0.2917          | 0.8881   |
| 0.1777        | 41.0  | 9266  | 0.2916          | 0.8865   |
| 0.2413        | 42.0  | 9492  | 0.2907          | 0.8881   |
| 0.2247        | 43.0  | 9718  | 0.2903          | 0.8865   |
| 0.1658        | 44.0  | 9944  | 0.2899          | 0.8881   |
| 0.2589        | 45.0  | 10170 | 0.2898          | 0.8865   |
| 0.2258        | 46.0  | 10396 | 0.2894          | 0.8881   |
| 0.2122        | 47.0  | 10622 | 0.2892          | 0.8881   |
| 0.2435        | 48.0  | 10848 | 0.2891          | 0.8881   |
| 0.1811        | 49.0  | 11074 | 0.2890          | 0.8881   |
| 0.2047        | 50.0  | 11300 | 0.2890          | 0.8881   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8881469115191987, "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