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# smids_3x_deit_base_sgd_001_fold2

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: 0.3164
- Accuracy: 0.8702

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9356        | 1.0   | 225   | 0.9551          | 0.6140   |
| 0.7266        | 2.0   | 450   | 0.7486          | 0.7288   |
| 0.5616        | 3.0   | 675   | 0.6080          | 0.7704   |
| 0.547         | 4.0   | 900   | 0.5262          | 0.7937   |
| 0.4582        | 5.0   | 1125  | 0.4769          | 0.7987   |
| 0.3947        | 6.0   | 1350  | 0.4429          | 0.8103   |
| 0.3972        | 7.0   | 1575  | 0.4203          | 0.8270   |
| 0.3767        | 8.0   | 1800  | 0.4042          | 0.8286   |
| 0.3401        | 9.0   | 2025  | 0.3910          | 0.8369   |
| 0.3023        | 10.0  | 2250  | 0.3806          | 0.8419   |
| 0.3373        | 11.0  | 2475  | 0.3718          | 0.8436   |
| 0.2966        | 12.0  | 2700  | 0.3663          | 0.8502   |
| 0.2871        | 13.0  | 2925  | 0.3599          | 0.8502   |
| 0.2823        | 14.0  | 3150  | 0.3565          | 0.8502   |
| 0.3247        | 15.0  | 3375  | 0.3500          | 0.8486   |
| 0.3466        | 16.0  | 3600  | 0.3478          | 0.8486   |
| 0.2808        | 17.0  | 3825  | 0.3471          | 0.8486   |
| 0.2148        | 18.0  | 4050  | 0.3407          | 0.8469   |
| 0.245         | 19.0  | 4275  | 0.3382          | 0.8502   |
| 0.2737        | 20.0  | 4500  | 0.3376          | 0.8486   |
| 0.2877        | 21.0  | 4725  | 0.3336          | 0.8486   |
| 0.3056        | 22.0  | 4950  | 0.3302          | 0.8502   |
| 0.3242        | 23.0  | 5175  | 0.3293          | 0.8519   |
| 0.2649        | 24.0  | 5400  | 0.3291          | 0.8536   |
| 0.2721        | 25.0  | 5625  | 0.3296          | 0.8519   |
| 0.2345        | 26.0  | 5850  | 0.3266          | 0.8519   |
| 0.2272        | 27.0  | 6075  | 0.3224          | 0.8586   |
| 0.2367        | 28.0  | 6300  | 0.3218          | 0.8569   |
| 0.2688        | 29.0  | 6525  | 0.3231          | 0.8552   |
| 0.2737        | 30.0  | 6750  | 0.3223          | 0.8569   |
| 0.2277        | 31.0  | 6975  | 0.3231          | 0.8602   |
| 0.2491        | 32.0  | 7200  | 0.3225          | 0.8602   |
| 0.2511        | 33.0  | 7425  | 0.3193          | 0.8602   |
| 0.2122        | 34.0  | 7650  | 0.3202          | 0.8569   |
| 0.2292        | 35.0  | 7875  | 0.3193          | 0.8602   |
| 0.243         | 36.0  | 8100  | 0.3185          | 0.8619   |
| 0.2358        | 37.0  | 8325  | 0.3187          | 0.8652   |
| 0.2127        | 38.0  | 8550  | 0.3178          | 0.8669   |
| 0.2259        | 39.0  | 8775  | 0.3182          | 0.8686   |
| 0.2023        | 40.0  | 9000  | 0.3176          | 0.8686   |
| 0.194         | 41.0  | 9225  | 0.3177          | 0.8686   |
| 0.2145        | 42.0  | 9450  | 0.3163          | 0.8669   |
| 0.188         | 43.0  | 9675  | 0.3174          | 0.8686   |
| 0.2222        | 44.0  | 9900  | 0.3170          | 0.8686   |
| 0.2664        | 45.0  | 10125 | 0.3165          | 0.8652   |
| 0.2195        | 46.0  | 10350 | 0.3166          | 0.8686   |
| 0.2046        | 47.0  | 10575 | 0.3165          | 0.8686   |
| 0.1994        | 48.0  | 10800 | 0.3164          | 0.8669   |
| 0.2327        | 49.0  | 11025 | 0.3164          | 0.8702   |
| 0.1935        | 50.0  | 11250 | 0.3164          | 0.8702   |


### 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_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.870216306156406, "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