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# smids_10x_deit_tiny_rms_001_fold1

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: 1.8993
- Accuracy: 0.8047

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8539        | 1.0   | 751   | 0.7969          | 0.6144   |
| 0.672         | 2.0   | 1502  | 0.7985          | 0.6194   |
| 0.6698        | 3.0   | 2253  | 0.6650          | 0.6962   |
| 0.6307        | 4.0   | 3004  | 0.6193          | 0.7379   |
| 0.6465        | 5.0   | 3755  | 0.8387          | 0.6244   |
| 0.6942        | 6.0   | 4506  | 0.5940          | 0.7329   |
| 0.5576        | 7.0   | 5257  | 0.5999          | 0.7312   |
| 0.5549        | 8.0   | 6008  | 0.6970          | 0.6795   |
| 0.5488        | 9.0   | 6759  | 0.5984          | 0.7229   |
| 0.5437        | 10.0  | 7510  | 0.5960          | 0.7412   |
| 0.5332        | 11.0  | 8261  | 0.5776          | 0.7362   |
| 0.5215        | 12.0  | 9012  | 0.5476          | 0.7880   |
| 0.5333        | 13.0  | 9763  | 0.5233          | 0.7713   |
| 0.4806        | 14.0  | 10514 | 0.5633          | 0.7629   |
| 0.4615        | 15.0  | 11265 | 0.5133          | 0.7830   |
| 0.535         | 16.0  | 12016 | 0.5400          | 0.7362   |
| 0.4592        | 17.0  | 12767 | 0.5660          | 0.7546   |
| 0.4186        | 18.0  | 13518 | 0.5267          | 0.7913   |
| 0.4986        | 19.0  | 14269 | 0.5193          | 0.7846   |
| 0.4777        | 20.0  | 15020 | 0.5053          | 0.7880   |
| 0.4305        | 21.0  | 15771 | 0.5032          | 0.7846   |
| 0.4268        | 22.0  | 16522 | 0.5151          | 0.7830   |
| 0.3969        | 23.0  | 17273 | 0.5356          | 0.7846   |
| 0.4042        | 24.0  | 18024 | 0.5574          | 0.7780   |
| 0.3889        | 25.0  | 18775 | 0.5262          | 0.7679   |
| 0.4127        | 26.0  | 19526 | 0.5352          | 0.7696   |
| 0.3984        | 27.0  | 20277 | 0.5102          | 0.7796   |
| 0.4155        | 28.0  | 21028 | 0.5170          | 0.8030   |
| 0.2889        | 29.0  | 21779 | 0.5194          | 0.8080   |
| 0.2798        | 30.0  | 22530 | 0.5140          | 0.8063   |
| 0.3345        | 31.0  | 23281 | 0.5542          | 0.8097   |
| 0.3266        | 32.0  | 24032 | 0.5467          | 0.7763   |
| 0.3139        | 33.0  | 24783 | 0.5408          | 0.8013   |
| 0.2727        | 34.0  | 25534 | 0.6157          | 0.7997   |
| 0.2326        | 35.0  | 26285 | 0.6453          | 0.8080   |
| 0.2862        | 36.0  | 27036 | 0.6184          | 0.8080   |
| 0.2315        | 37.0  | 27787 | 0.5988          | 0.8097   |
| 0.2292        | 38.0  | 28538 | 0.5807          | 0.8164   |
| 0.1347        | 39.0  | 29289 | 0.6678          | 0.8247   |
| 0.2469        | 40.0  | 30040 | 0.7259          | 0.8080   |
| 0.1108        | 41.0  | 30791 | 0.8996          | 0.7813   |
| 0.1298        | 42.0  | 31542 | 0.8857          | 0.8247   |
| 0.1746        | 43.0  | 32293 | 0.9061          | 0.8197   |
| 0.0873        | 44.0  | 33044 | 1.0379          | 0.8230   |
| 0.087         | 45.0  | 33795 | 1.2137          | 0.8130   |
| 0.1277        | 46.0  | 34546 | 1.3333          | 0.8197   |
| 0.069         | 47.0  | 35297 | 1.4653          | 0.8164   |
| 0.0206        | 48.0  | 36048 | 1.6979          | 0.8063   |
| 0.0279        | 49.0  | 36799 | 1.8534          | 0.8063   |
| 0.02          | 50.0  | 37550 | 1.8993          | 0.8047   |


### 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_10x_deit_tiny_rms_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": 0.8046744574290484, "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