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# hushem_1x_deit_small_rms_00001_fold1

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8886
- Accuracy: 0.6889

## 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: 1e-05
- 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    | 1.2079          | 0.6      |
| 1.2767        | 2.0   | 12   | 1.0689          | 0.5778   |
| 1.2767        | 3.0   | 18   | 0.8710          | 0.7111   |
| 0.496         | 4.0   | 24   | 0.7898          | 0.7111   |
| 0.172         | 5.0   | 30   | 0.8332          | 0.6889   |
| 0.172         | 6.0   | 36   | 1.0763          | 0.5556   |
| 0.0549        | 7.0   | 42   | 0.6935          | 0.7556   |
| 0.0549        | 8.0   | 48   | 0.7853          | 0.6667   |
| 0.0174        | 9.0   | 54   | 0.7910          | 0.6889   |
| 0.0066        | 10.0  | 60   | 0.7721          | 0.7111   |
| 0.0066        | 11.0  | 66   | 0.7433          | 0.6889   |
| 0.0038        | 12.0  | 72   | 0.7425          | 0.6889   |
| 0.0038        | 13.0  | 78   | 0.7897          | 0.6667   |
| 0.003         | 14.0  | 84   | 0.8070          | 0.6889   |
| 0.0022        | 15.0  | 90   | 0.8283          | 0.6889   |
| 0.0022        | 16.0  | 96   | 0.8010          | 0.6889   |
| 0.0019        | 17.0  | 102  | 0.8154          | 0.6889   |
| 0.0019        | 18.0  | 108  | 0.8316          | 0.6889   |
| 0.0016        | 19.0  | 114  | 0.8425          | 0.6889   |
| 0.0014        | 20.0  | 120  | 0.8372          | 0.6889   |
| 0.0014        | 21.0  | 126  | 0.8392          | 0.6889   |
| 0.0013        | 22.0  | 132  | 0.8471          | 0.6889   |
| 0.0013        | 23.0  | 138  | 0.8542          | 0.7111   |
| 0.0012        | 24.0  | 144  | 0.8532          | 0.6889   |
| 0.001         | 25.0  | 150  | 0.8592          | 0.6889   |
| 0.001         | 26.0  | 156  | 0.8620          | 0.6889   |
| 0.001         | 27.0  | 162  | 0.8623          | 0.6889   |
| 0.001         | 28.0  | 168  | 0.8684          | 0.6889   |
| 0.0009        | 29.0  | 174  | 0.8656          | 0.6667   |
| 0.0009        | 30.0  | 180  | 0.8670          | 0.6889   |
| 0.0009        | 31.0  | 186  | 0.8710          | 0.6889   |
| 0.0008        | 32.0  | 192  | 0.8750          | 0.6889   |
| 0.0008        | 33.0  | 198  | 0.8785          | 0.6667   |
| 0.0008        | 34.0  | 204  | 0.8810          | 0.6667   |
| 0.0008        | 35.0  | 210  | 0.8827          | 0.6667   |
| 0.0008        | 36.0  | 216  | 0.8847          | 0.6889   |
| 0.0007        | 37.0  | 222  | 0.8870          | 0.6889   |
| 0.0007        | 38.0  | 228  | 0.8890          | 0.6889   |
| 0.0007        | 39.0  | 234  | 0.8882          | 0.6889   |
| 0.0007        | 40.0  | 240  | 0.8885          | 0.6889   |
| 0.0007        | 41.0  | 246  | 0.8887          | 0.6889   |
| 0.0007        | 42.0  | 252  | 0.8886          | 0.6889   |
| 0.0007        | 43.0  | 258  | 0.8886          | 0.6889   |
| 0.0007        | 44.0  | 264  | 0.8886          | 0.6889   |
| 0.0007        | 45.0  | 270  | 0.8886          | 0.6889   |
| 0.0007        | 46.0  | 276  | 0.8886          | 0.6889   |
| 0.0007        | 47.0  | 282  | 0.8886          | 0.6889   |
| 0.0007        | 48.0  | 288  | 0.8886          | 0.6889   |
| 0.0007        | 49.0  | 294  | 0.8886          | 0.6889   |
| 0.0007        | 50.0  | 300  | 0.8886          | 0.6889   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-small-patch16-224", "model-index": [{"name": "hushem_1x_deit_small_rms_00001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6888888888888889, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us