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# smids_3x_deit_tiny_rms_001_fold2

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9828
- Accuracy: 0.8037

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8903        | 1.0   | 225   | 0.8221          | 0.5707   |
| 0.8376        | 2.0   | 450   | 0.7917          | 0.6023   |
| 0.7073        | 3.0   | 675   | 0.7643          | 0.5790   |
| 0.7158        | 4.0   | 900   | 0.7590          | 0.6506   |
| 0.6892        | 5.0   | 1125  | 0.7293          | 0.6506   |
| 0.6685        | 6.0   | 1350  | 0.6489          | 0.6755   |
| 0.606         | 7.0   | 1575  | 0.5908          | 0.7471   |
| 0.6652        | 8.0   | 1800  | 0.5586          | 0.7537   |
| 0.6311        | 9.0   | 2025  | 0.5971          | 0.7504   |
| 0.5645        | 10.0  | 2250  | 0.5700          | 0.7571   |
| 0.6575        | 11.0  | 2475  | 0.6329          | 0.7338   |
| 0.5727        | 12.0  | 2700  | 0.5598          | 0.7521   |
| 0.5704        | 13.0  | 2925  | 0.5359          | 0.7754   |
| 0.5215        | 14.0  | 3150  | 0.5587          | 0.7571   |
| 0.583         | 15.0  | 3375  | 0.5430          | 0.7787   |
| 0.5848        | 16.0  | 3600  | 0.5789          | 0.7255   |
| 0.5726        | 17.0  | 3825  | 0.5236          | 0.7854   |
| 0.489         | 18.0  | 4050  | 0.4992          | 0.8003   |
| 0.4753        | 19.0  | 4275  | 0.5863          | 0.7621   |
| 0.5263        | 20.0  | 4500  | 0.5219          | 0.7704   |
| 0.4735        | 21.0  | 4725  | 0.4900          | 0.7970   |
| 0.5712        | 22.0  | 4950  | 0.5240          | 0.8070   |
| 0.5071        | 23.0  | 5175  | 0.5142          | 0.7854   |
| 0.5079        | 24.0  | 5400  | 0.5416          | 0.7887   |
| 0.4923        | 25.0  | 5625  | 0.5063          | 0.8053   |
| 0.3927        | 26.0  | 5850  | 0.5633          | 0.7870   |
| 0.3745        | 27.0  | 6075  | 0.6375          | 0.7621   |
| 0.3879        | 28.0  | 6300  | 0.5787          | 0.7787   |
| 0.3817        | 29.0  | 6525  | 0.5796          | 0.7887   |
| 0.3478        | 30.0  | 6750  | 0.5474          | 0.8070   |
| 0.3866        | 31.0  | 6975  | 0.5776          | 0.7920   |
| 0.3993        | 32.0  | 7200  | 0.5703          | 0.8103   |
| 0.2926        | 33.0  | 7425  | 0.6089          | 0.7970   |
| 0.2772        | 34.0  | 7650  | 0.6185          | 0.8020   |
| 0.2754        | 35.0  | 7875  | 0.6777          | 0.7854   |
| 0.2402        | 36.0  | 8100  | 0.7422          | 0.7870   |
| 0.2412        | 37.0  | 8325  | 0.7873          | 0.7754   |
| 0.2165        | 38.0  | 8550  | 0.8318          | 0.8070   |
| 0.1829        | 39.0  | 8775  | 0.8522          | 0.7920   |
| 0.1669        | 40.0  | 9000  | 0.9913          | 0.7903   |
| 0.135         | 41.0  | 9225  | 1.0029          | 0.8003   |
| 0.1443        | 42.0  | 9450  | 1.0999          | 0.7987   |
| 0.0893        | 43.0  | 9675  | 1.2541          | 0.8020   |
| 0.0533        | 44.0  | 9900  | 1.3854          | 0.8003   |
| 0.065         | 45.0  | 10125 | 1.6713          | 0.7754   |
| 0.0332        | 46.0  | 10350 | 1.6089          | 0.8003   |
| 0.0177        | 47.0  | 10575 | 1.8304          | 0.7920   |
| 0.0017        | 48.0  | 10800 | 1.9277          | 0.7937   |
| 0.0154        | 49.0  | 11025 | 1.9904          | 0.8053   |
| 0.0079        | 50.0  | 11250 | 1.9828          | 0.8037   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+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-tiny-patch16-224", "model-index": [{"name": "smids_3x_deit_tiny_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": 0.8036605657237936, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us