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# hushem_40x_deit_tiny_rms_001_fold3

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: 2.2392
- Accuracy: 0.7907

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.246         | 1.0   | 217   | 1.4100          | 0.2558   |
| 0.9627        | 2.0   | 434   | 1.1709          | 0.5116   |
| 0.8333        | 3.0   | 651   | 1.1793          | 0.4186   |
| 0.7844        | 4.0   | 868   | 0.8077          | 0.6279   |
| 0.7035        | 5.0   | 1085  | 1.3327          | 0.5116   |
| 0.7976        | 6.0   | 1302  | 0.7941          | 0.6977   |
| 0.7352        | 7.0   | 1519  | 0.9909          | 0.6279   |
| 0.6247        | 8.0   | 1736  | 0.7281          | 0.6977   |
| 0.6212        | 9.0   | 1953  | 1.1902          | 0.6279   |
| 0.6647        | 10.0  | 2170  | 1.0897          | 0.5581   |
| 0.4763        | 11.0  | 2387  | 0.9383          | 0.6047   |
| 0.5076        | 12.0  | 2604  | 0.5861          | 0.7907   |
| 0.4573        | 13.0  | 2821  | 0.9438          | 0.5349   |
| 0.3857        | 14.0  | 3038  | 0.7991          | 0.6977   |
| 0.3919        | 15.0  | 3255  | 0.9377          | 0.6047   |
| 0.352         | 16.0  | 3472  | 1.0859          | 0.5814   |
| 0.3551        | 17.0  | 3689  | 1.2113          | 0.6744   |
| 0.3196        | 18.0  | 3906  | 1.2889          | 0.6279   |
| 0.2405        | 19.0  | 4123  | 0.9915          | 0.6512   |
| 0.2367        | 20.0  | 4340  | 1.6136          | 0.6279   |
| 0.2222        | 21.0  | 4557  | 1.4836          | 0.5814   |
| 0.1901        | 22.0  | 4774  | 1.0739          | 0.7209   |
| 0.173         | 23.0  | 4991  | 1.3956          | 0.6512   |
| 0.1711        | 24.0  | 5208  | 1.7072          | 0.6279   |
| 0.1027        | 25.0  | 5425  | 1.4657          | 0.6512   |
| 0.0952        | 26.0  | 5642  | 1.6372          | 0.6744   |
| 0.1462        | 27.0  | 5859  | 2.2566          | 0.5814   |
| 0.1003        | 28.0  | 6076  | 1.5093          | 0.6512   |
| 0.0764        | 29.0  | 6293  | 1.9318          | 0.6512   |
| 0.1025        | 30.0  | 6510  | 1.9630          | 0.6047   |
| 0.0702        | 31.0  | 6727  | 2.1273          | 0.6512   |
| 0.0313        | 32.0  | 6944  | 1.6171          | 0.7209   |
| 0.0732        | 33.0  | 7161  | 1.2147          | 0.7209   |
| 0.0384        | 34.0  | 7378  | 1.9804          | 0.7209   |
| 0.0177        | 35.0  | 7595  | 1.8221          | 0.6512   |
| 0.0098        | 36.0  | 7812  | 2.4941          | 0.6744   |
| 0.0407        | 37.0  | 8029  | 2.6063          | 0.6512   |
| 0.0798        | 38.0  | 8246  | 3.5391          | 0.5581   |
| 0.0022        | 39.0  | 8463  | 2.7971          | 0.6512   |
| 0.0004        | 40.0  | 8680  | 1.8602          | 0.7209   |
| 0.0547        | 41.0  | 8897  | 2.4427          | 0.6744   |
| 0.0003        | 42.0  | 9114  | 2.1061          | 0.6977   |
| 0.0003        | 43.0  | 9331  | 2.0283          | 0.5814   |
| 0.0017        | 44.0  | 9548  | 2.1926          | 0.6744   |
| 0.0001        | 45.0  | 9765  | 1.9704          | 0.7674   |
| 0.0           | 46.0  | 9982  | 2.2645          | 0.7442   |
| 0.0001        | 47.0  | 10199 | 2.3408          | 0.7674   |
| 0.0           | 48.0  | 10416 | 2.2312          | 0.7674   |
| 0.0           | 49.0  | 10633 | 2.2302          | 0.7907   |
| 0.0           | 50.0  | 10850 | 2.2392          | 0.7907   |


### 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_rms_001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7906976744186046, "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