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# smids_3x_deit_base_sgd_001_fold4

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: 0.3344
- Accuracy: 0.8767

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9564        | 1.0   | 225   | 0.9423          | 0.64     |
| 0.7113        | 2.0   | 450   | 0.7214          | 0.7733   |
| 0.5639        | 3.0   | 675   | 0.5832          | 0.8017   |
| 0.5094        | 4.0   | 900   | 0.5049          | 0.8183   |
| 0.4968        | 5.0   | 1125  | 0.4596          | 0.825    |
| 0.3617        | 6.0   | 1350  | 0.4304          | 0.8383   |
| 0.4108        | 7.0   | 1575  | 0.4105          | 0.84     |
| 0.4388        | 8.0   | 1800  | 0.3975          | 0.845    |
| 0.3859        | 9.0   | 2025  | 0.3855          | 0.845    |
| 0.3342        | 10.0  | 2250  | 0.3790          | 0.85     |
| 0.3561        | 11.0  | 2475  | 0.3717          | 0.8533   |
| 0.3675        | 12.0  | 2700  | 0.3673          | 0.855    |
| 0.2823        | 13.0  | 2925  | 0.3617          | 0.86     |
| 0.2556        | 14.0  | 3150  | 0.3581          | 0.8583   |
| 0.2719        | 15.0  | 3375  | 0.3554          | 0.86     |
| 0.2758        | 16.0  | 3600  | 0.3520          | 0.86     |
| 0.2583        | 17.0  | 3825  | 0.3508          | 0.8617   |
| 0.2892        | 18.0  | 4050  | 0.3484          | 0.8633   |
| 0.3042        | 19.0  | 4275  | 0.3478          | 0.8683   |
| 0.2293        | 20.0  | 4500  | 0.3445          | 0.8667   |
| 0.2549        | 21.0  | 4725  | 0.3434          | 0.8717   |
| 0.2441        | 22.0  | 4950  | 0.3424          | 0.8683   |
| 0.2463        | 23.0  | 5175  | 0.3417          | 0.8683   |
| 0.2314        | 24.0  | 5400  | 0.3394          | 0.8667   |
| 0.2319        | 25.0  | 5625  | 0.3388          | 0.8683   |
| 0.2172        | 26.0  | 5850  | 0.3384          | 0.8667   |
| 0.2256        | 27.0  | 6075  | 0.3381          | 0.8667   |
| 0.212         | 28.0  | 6300  | 0.3381          | 0.8683   |
| 0.1974        | 29.0  | 6525  | 0.3386          | 0.87     |
| 0.2121        | 30.0  | 6750  | 0.3373          | 0.8683   |
| 0.2143        | 31.0  | 6975  | 0.3372          | 0.87     |
| 0.2062        | 32.0  | 7200  | 0.3362          | 0.8717   |
| 0.2495        | 33.0  | 7425  | 0.3366          | 0.8717   |
| 0.1945        | 34.0  | 7650  | 0.3360          | 0.8733   |
| 0.203         | 35.0  | 7875  | 0.3362          | 0.8717   |
| 0.2268        | 36.0  | 8100  | 0.3356          | 0.875    |
| 0.1902        | 37.0  | 8325  | 0.3348          | 0.8733   |
| 0.2187        | 38.0  | 8550  | 0.3349          | 0.875    |
| 0.2032        | 39.0  | 8775  | 0.3350          | 0.875    |
| 0.2156        | 40.0  | 9000  | 0.3342          | 0.875    |
| 0.2119        | 41.0  | 9225  | 0.3346          | 0.8767   |
| 0.2354        | 42.0  | 9450  | 0.3345          | 0.8767   |
| 0.1983        | 43.0  | 9675  | 0.3345          | 0.8767   |
| 0.2529        | 44.0  | 9900  | 0.3343          | 0.8767   |
| 0.2248        | 45.0  | 10125 | 0.3345          | 0.875    |
| 0.2133        | 46.0  | 10350 | 0.3343          | 0.8767   |
| 0.2026        | 47.0  | 10575 | 0.3344          | 0.8767   |
| 0.2376        | 48.0  | 10800 | 0.3344          | 0.8767   |
| 0.241         | 49.0  | 11025 | 0.3344          | 0.8767   |
| 0.2159        | 50.0  | 11250 | 0.3344          | 0.8767   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8766666666666667, "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