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# hushem_40x_deit_tiny_sgd_001_fold4

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: 0.2388
- Accuracy: 0.8810

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2231        | 1.0   | 219   | 1.3846          | 0.2857   |
| 0.9485        | 2.0   | 438   | 1.1776          | 0.5238   |
| 0.8421        | 3.0   | 657   | 0.9985          | 0.6429   |
| 0.6802        | 4.0   | 876   | 0.8236          | 0.7381   |
| 0.5815        | 5.0   | 1095  | 0.6866          | 0.7857   |
| 0.5091        | 6.0   | 1314  | 0.5853          | 0.8095   |
| 0.3792        | 7.0   | 1533  | 0.5105          | 0.8333   |
| 0.3552        | 8.0   | 1752  | 0.4443          | 0.8333   |
| 0.3174        | 9.0   | 1971  | 0.4029          | 0.8810   |
| 0.2621        | 10.0  | 2190  | 0.3730          | 0.8571   |
| 0.2168        | 11.0  | 2409  | 0.3473          | 0.8571   |
| 0.2263        | 12.0  | 2628  | 0.3296          | 0.9048   |
| 0.1689        | 13.0  | 2847  | 0.3233          | 0.9048   |
| 0.171         | 14.0  | 3066  | 0.3040          | 0.8810   |
| 0.1176        | 15.0  | 3285  | 0.3059          | 0.8810   |
| 0.1241        | 16.0  | 3504  | 0.2811          | 0.8571   |
| 0.1343        | 17.0  | 3723  | 0.2712          | 0.8571   |
| 0.0953        | 18.0  | 3942  | 0.2802          | 0.8571   |
| 0.0918        | 19.0  | 4161  | 0.2700          | 0.8571   |
| 0.0691        | 20.0  | 4380  | 0.2755          | 0.8571   |
| 0.088         | 21.0  | 4599  | 0.2615          | 0.8571   |
| 0.0857        | 22.0  | 4818  | 0.2483          | 0.8571   |
| 0.0654        | 23.0  | 5037  | 0.2562          | 0.8571   |
| 0.0661        | 24.0  | 5256  | 0.2789          | 0.8571   |
| 0.0463        | 25.0  | 5475  | 0.2435          | 0.8571   |
| 0.0362        | 26.0  | 5694  | 0.2633          | 0.8571   |
| 0.0272        | 27.0  | 5913  | 0.2844          | 0.8571   |
| 0.041         | 28.0  | 6132  | 0.2942          | 0.8571   |
| 0.034         | 29.0  | 6351  | 0.2744          | 0.8571   |
| 0.0352        | 30.0  | 6570  | 0.2644          | 0.8810   |
| 0.0212        | 31.0  | 6789  | 0.2648          | 0.8810   |
| 0.0359        | 32.0  | 7008  | 0.2431          | 0.8810   |
| 0.0203        | 33.0  | 7227  | 0.2434          | 0.8810   |
| 0.0209        | 34.0  | 7446  | 0.2577          | 0.8810   |
| 0.0254        | 35.0  | 7665  | 0.2645          | 0.8810   |
| 0.0178        | 36.0  | 7884  | 0.2497          | 0.8810   |
| 0.0232        | 37.0  | 8103  | 0.2639          | 0.8810   |
| 0.015         | 38.0  | 8322  | 0.2391          | 0.8810   |
| 0.0246        | 39.0  | 8541  | 0.2615          | 0.8810   |
| 0.0228        | 40.0  | 8760  | 0.2445          | 0.8810   |
| 0.0203        | 41.0  | 8979  | 0.2448          | 0.8810   |
| 0.014         | 42.0  | 9198  | 0.2402          | 0.8810   |
| 0.0231        | 43.0  | 9417  | 0.2372          | 0.8810   |
| 0.0179        | 44.0  | 9636  | 0.2499          | 0.8810   |
| 0.0197        | 45.0  | 9855  | 0.2540          | 0.8810   |
| 0.0118        | 46.0  | 10074 | 0.2416          | 0.8810   |
| 0.0134        | 47.0  | 10293 | 0.2401          | 0.8810   |
| 0.0155        | 48.0  | 10512 | 0.2412          | 0.8810   |
| 0.0103        | 49.0  | 10731 | 0.2400          | 0.8810   |
| 0.0156        | 50.0  | 10950 | 0.2388          | 0.8810   |


### 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": "hushem_40x_deit_tiny_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": 0.8809523809523809, "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