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# smids_10x_deit_tiny_sgd_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: 0.3411
- Accuracy: 0.8715

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5089        | 1.0   | 751   | 0.6112          | 0.7429   |
| 0.3967        | 2.0   | 1502  | 0.4763          | 0.7930   |
| 0.2926        | 3.0   | 2253  | 0.3983          | 0.8314   |
| 0.2707        | 4.0   | 3004  | 0.3655          | 0.8431   |
| 0.3017        | 5.0   | 3755  | 0.3388          | 0.8598   |
| 0.2883        | 6.0   | 4506  | 0.3239          | 0.8581   |
| 0.2607        | 7.0   | 5257  | 0.3147          | 0.8681   |
| 0.2345        | 8.0   | 6008  | 0.3166          | 0.8564   |
| 0.2342        | 9.0   | 6759  | 0.3080          | 0.8765   |
| 0.2448        | 10.0  | 7510  | 0.3026          | 0.8715   |
| 0.2489        | 11.0  | 8261  | 0.3046          | 0.8664   |
| 0.2253        | 12.0  | 9012  | 0.3048          | 0.8731   |
| 0.1846        | 13.0  | 9763  | 0.3033          | 0.8681   |
| 0.1475        | 14.0  | 10514 | 0.3005          | 0.8698   |
| 0.1911        | 15.0  | 11265 | 0.2987          | 0.8731   |
| 0.1765        | 16.0  | 12016 | 0.3037          | 0.8664   |
| 0.2371        | 17.0  | 12767 | 0.3023          | 0.8698   |
| 0.1758        | 18.0  | 13518 | 0.3012          | 0.8731   |
| 0.2258        | 19.0  | 14269 | 0.3050          | 0.8698   |
| 0.1902        | 20.0  | 15020 | 0.3050          | 0.8681   |
| 0.1077        | 21.0  | 15771 | 0.3133          | 0.8698   |
| 0.1647        | 22.0  | 16522 | 0.3182          | 0.8715   |
| 0.1389        | 23.0  | 17273 | 0.3149          | 0.8731   |
| 0.1858        | 24.0  | 18024 | 0.3136          | 0.8664   |
| 0.1711        | 25.0  | 18775 | 0.3139          | 0.8631   |
| 0.191         | 26.0  | 19526 | 0.3138          | 0.8648   |
| 0.181         | 27.0  | 20277 | 0.3209          | 0.8715   |
| 0.2185        | 28.0  | 21028 | 0.3215          | 0.8748   |
| 0.1776        | 29.0  | 21779 | 0.3185          | 0.8715   |
| 0.135         | 30.0  | 22530 | 0.3255          | 0.8681   |
| 0.1282        | 31.0  | 23281 | 0.3235          | 0.8715   |
| 0.1784        | 32.0  | 24032 | 0.3244          | 0.8698   |
| 0.2006        | 33.0  | 24783 | 0.3311          | 0.8581   |
| 0.106         | 34.0  | 25534 | 0.3280          | 0.8715   |
| 0.1426        | 35.0  | 26285 | 0.3297          | 0.8681   |
| 0.1309        | 36.0  | 27036 | 0.3304          | 0.8614   |
| 0.2379        | 37.0  | 27787 | 0.3292          | 0.8748   |
| 0.1297        | 38.0  | 28538 | 0.3352          | 0.8698   |
| 0.0635        | 39.0  | 29289 | 0.3365          | 0.8664   |
| 0.1936        | 40.0  | 30040 | 0.3376          | 0.8698   |
| 0.1143        | 41.0  | 30791 | 0.3368          | 0.8731   |
| 0.1251        | 42.0  | 31542 | 0.3385          | 0.8664   |
| 0.1338        | 43.0  | 32293 | 0.3411          | 0.8681   |
| 0.1093        | 44.0  | 33044 | 0.3395          | 0.8681   |
| 0.1208        | 45.0  | 33795 | 0.3395          | 0.8715   |
| 0.1467        | 46.0  | 34546 | 0.3416          | 0.8698   |
| 0.0894        | 47.0  | 35297 | 0.3413          | 0.8698   |
| 0.1318        | 48.0  | 36048 | 0.3412          | 0.8681   |
| 0.0983        | 49.0  | 36799 | 0.3410          | 0.8715   |
| 0.1226        | 50.0  | 37550 | 0.3411          | 0.8715   |


### 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_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": 0.8714524207011686, "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