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# hushem_1x_deit_tiny_rms_0001_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: 2.2114
- Accuracy: 0.5814

## 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: 0.0001
- 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    | 1.4590          | 0.2558   |
| 2.1915        | 2.0   | 12   | 1.4820          | 0.2558   |
| 2.1915        | 3.0   | 18   | 1.4635          | 0.3488   |
| 1.4733        | 4.0   | 24   | 1.6507          | 0.2558   |
| 1.4003        | 5.0   | 30   | 1.5038          | 0.2558   |
| 1.4003        | 6.0   | 36   | 1.5372          | 0.2093   |
| 1.28          | 7.0   | 42   | 1.4420          | 0.3023   |
| 1.28          | 8.0   | 48   | 1.3681          | 0.3488   |
| 1.2064        | 9.0   | 54   | 1.4133          | 0.3023   |
| 1.1588        | 10.0  | 60   | 1.2991          | 0.4419   |
| 1.1588        | 11.0  | 66   | 1.2547          | 0.4651   |
| 1.133         | 12.0  | 72   | 1.2924          | 0.4884   |
| 1.133         | 13.0  | 78   | 1.2566          | 0.4884   |
| 1.0357        | 14.0  | 84   | 1.1915          | 0.5349   |
| 0.8616        | 15.0  | 90   | 1.2058          | 0.5116   |
| 0.8616        | 16.0  | 96   | 1.1399          | 0.5349   |
| 0.6595        | 17.0  | 102  | 1.1462          | 0.5581   |
| 0.6595        | 18.0  | 108  | 1.2856          | 0.5116   |
| 0.501         | 19.0  | 114  | 1.1528          | 0.6047   |
| 0.3761        | 20.0  | 120  | 1.2487          | 0.6047   |
| 0.3761        | 21.0  | 126  | 1.9335          | 0.5581   |
| 0.1818        | 22.0  | 132  | 2.0855          | 0.5349   |
| 0.1818        | 23.0  | 138  | 2.8198          | 0.5349   |
| 0.0677        | 24.0  | 144  | 1.5837          | 0.6279   |
| 0.0703        | 25.0  | 150  | 2.1739          | 0.5116   |
| 0.0703        | 26.0  | 156  | 2.0640          | 0.5581   |
| 0.0053        | 27.0  | 162  | 2.0886          | 0.5814   |
| 0.0053        | 28.0  | 168  | 2.1352          | 0.5814   |
| 0.0006        | 29.0  | 174  | 2.1434          | 0.5814   |
| 0.0004        | 30.0  | 180  | 2.1524          | 0.5814   |
| 0.0004        | 31.0  | 186  | 2.1594          | 0.5814   |
| 0.0003        | 32.0  | 192  | 2.1659          | 0.5814   |
| 0.0003        | 33.0  | 198  | 2.1759          | 0.5814   |
| 0.0003        | 34.0  | 204  | 2.1825          | 0.5814   |
| 0.0003        | 35.0  | 210  | 2.1918          | 0.5814   |
| 0.0003        | 36.0  | 216  | 2.1964          | 0.5814   |
| 0.0002        | 37.0  | 222  | 2.2014          | 0.5814   |
| 0.0002        | 38.0  | 228  | 2.2049          | 0.5814   |
| 0.0002        | 39.0  | 234  | 2.2075          | 0.5814   |
| 0.0002        | 40.0  | 240  | 2.2099          | 0.5814   |
| 0.0002        | 41.0  | 246  | 2.2110          | 0.5814   |
| 0.0002        | 42.0  | 252  | 2.2114          | 0.5814   |
| 0.0002        | 43.0  | 258  | 2.2114          | 0.5814   |
| 0.0002        | 44.0  | 264  | 2.2114          | 0.5814   |
| 0.0002        | 45.0  | 270  | 2.2114          | 0.5814   |
| 0.0002        | 46.0  | 276  | 2.2114          | 0.5814   |
| 0.0002        | 47.0  | 282  | 2.2114          | 0.5814   |
| 0.0002        | 48.0  | 288  | 2.2114          | 0.5814   |
| 0.0002        | 49.0  | 294  | 2.2114          | 0.5814   |
| 0.0002        | 50.0  | 300  | 2.2114          | 0.5814   |


### 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_0001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5813953488372093, "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