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# hushem_1x_deit_tiny_rms_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: 1.0712
- Accuracy: 0.4762

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 5.0165          | 0.2381   |
| 4.2481        | 2.0   | 12   | 3.3074          | 0.2381   |
| 4.2481        | 3.0   | 18   | 1.5288          | 0.2619   |
| 2.0024        | 4.0   | 24   | 1.5375          | 0.2381   |
| 1.6731        | 5.0   | 30   | 1.4069          | 0.2619   |
| 1.6731        | 6.0   | 36   | 1.8969          | 0.2381   |
| 1.5329        | 7.0   | 42   | 1.4811          | 0.2381   |
| 1.5329        | 8.0   | 48   | 1.4117          | 0.2619   |
| 1.475         | 9.0   | 54   | 1.4704          | 0.2619   |
| 1.4639        | 10.0  | 60   | 1.4459          | 0.2381   |
| 1.4639        | 11.0  | 66   | 1.3572          | 0.4524   |
| 1.4524        | 12.0  | 72   | 1.2630          | 0.4524   |
| 1.4524        | 13.0  | 78   | 1.2843          | 0.4524   |
| 1.4025        | 14.0  | 84   | 1.3420          | 0.2857   |
| 1.3666        | 15.0  | 90   | 1.4060          | 0.2381   |
| 1.3666        | 16.0  | 96   | 1.2621          | 0.3810   |
| 1.3178        | 17.0  | 102  | 1.2969          | 0.2857   |
| 1.3178        | 18.0  | 108  | 1.2881          | 0.3333   |
| 1.3667        | 19.0  | 114  | 1.3980          | 0.2857   |
| 1.3043        | 20.0  | 120  | 1.5195          | 0.2857   |
| 1.3043        | 21.0  | 126  | 1.1841          | 0.4048   |
| 1.2859        | 22.0  | 132  | 1.0567          | 0.5238   |
| 1.2859        | 23.0  | 138  | 1.2258          | 0.2619   |
| 1.2496        | 24.0  | 144  | 1.2372          | 0.2857   |
| 1.252         | 25.0  | 150  | 1.4386          | 0.3333   |
| 1.252         | 26.0  | 156  | 1.1416          | 0.3810   |
| 1.2296        | 27.0  | 162  | 1.0872          | 0.4286   |
| 1.2296        | 28.0  | 168  | 1.4121          | 0.2857   |
| 1.1581        | 29.0  | 174  | 1.0555          | 0.5476   |
| 1.2027        | 30.0  | 180  | 1.1296          | 0.4762   |
| 1.2027        | 31.0  | 186  | 1.2095          | 0.4048   |
| 1.1595        | 32.0  | 192  | 1.0821          | 0.4762   |
| 1.1595        | 33.0  | 198  | 1.1681          | 0.3810   |
| 1.1909        | 34.0  | 204  | 1.1147          | 0.4762   |
| 1.1121        | 35.0  | 210  | 1.0734          | 0.4048   |
| 1.1121        | 36.0  | 216  | 1.0002          | 0.5238   |
| 1.1218        | 37.0  | 222  | 1.1912          | 0.3095   |
| 1.1218        | 38.0  | 228  | 1.0883          | 0.4524   |
| 1.1024        | 39.0  | 234  | 1.1229          | 0.4286   |
| 1.0678        | 40.0  | 240  | 1.0903          | 0.4762   |
| 1.0678        | 41.0  | 246  | 1.0717          | 0.4762   |
| 1.058         | 42.0  | 252  | 1.0712          | 0.4762   |
| 1.058         | 43.0  | 258  | 1.0712          | 0.4762   |
| 1.0512        | 44.0  | 264  | 1.0712          | 0.4762   |
| 1.0743        | 45.0  | 270  | 1.0712          | 0.4762   |
| 1.0743        | 46.0  | 276  | 1.0712          | 0.4762   |
| 1.0691        | 47.0  | 282  | 1.0712          | 0.4762   |
| 1.0691        | 48.0  | 288  | 1.0712          | 0.4762   |
| 1.052         | 49.0  | 294  | 1.0712          | 0.4762   |
| 1.066         | 50.0  | 300  | 1.0712          | 0.4762   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "hushem_1x_deit_tiny_rms_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": 0.47619047619047616, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors 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