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# hushem_1x_deit_base_rms_001_fold5

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3674
- Accuracy: 0.4878

## 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    | 5.8345          | 0.2683   |
| 4.8133        | 2.0   | 12   | 1.9738          | 0.2439   |
| 4.8133        | 3.0   | 18   | 1.6557          | 0.2439   |
| 2.3825        | 4.0   | 24   | 1.4419          | 0.2439   |
| 1.6511        | 5.0   | 30   | 1.5141          | 0.2439   |
| 1.6511        | 6.0   | 36   | 1.7332          | 0.2683   |
| 1.5506        | 7.0   | 42   | 1.4915          | 0.2439   |
| 1.5506        | 8.0   | 48   | 1.4901          | 0.2683   |
| 1.4941        | 9.0   | 54   | 1.4008          | 0.2683   |
| 1.5024        | 10.0  | 60   | 1.4017          | 0.2439   |
| 1.5024        | 11.0  | 66   | 1.4108          | 0.2683   |
| 1.6905        | 12.0  | 72   | 1.4762          | 0.2439   |
| 1.6905        | 13.0  | 78   | 1.4772          | 0.2439   |
| 1.4363        | 14.0  | 84   | 1.3917          | 0.3659   |
| 1.4324        | 15.0  | 90   | 1.3778          | 0.2439   |
| 1.4324        | 16.0  | 96   | 1.4917          | 0.2439   |
| 1.4176        | 17.0  | 102  | 1.8605          | 0.2439   |
| 1.4176        | 18.0  | 108  | 1.2587          | 0.4634   |
| 1.4153        | 19.0  | 114  | 1.3519          | 0.3171   |
| 1.363         | 20.0  | 120  | 1.2976          | 0.3902   |
| 1.363         | 21.0  | 126  | 1.7214          | 0.3902   |
| 1.2297        | 22.0  | 132  | 1.5932          | 0.3415   |
| 1.2297        | 23.0  | 138  | 1.0760          | 0.5122   |
| 1.1323        | 24.0  | 144  | 1.1518          | 0.4390   |
| 1.0463        | 25.0  | 150  | 1.1823          | 0.4146   |
| 1.0463        | 26.0  | 156  | 1.0632          | 0.4634   |
| 1.0497        | 27.0  | 162  | 1.1057          | 0.5122   |
| 1.0497        | 28.0  | 168  | 0.9873          | 0.4390   |
| 0.9597        | 29.0  | 174  | 1.0710          | 0.5122   |
| 1.0006        | 30.0  | 180  | 1.1482          | 0.4146   |
| 1.0006        | 31.0  | 186  | 1.1124          | 0.4634   |
| 0.934         | 32.0  | 192  | 1.1437          | 0.4146   |
| 0.934         | 33.0  | 198  | 1.1241          | 0.4390   |
| 0.8599        | 34.0  | 204  | 1.1438          | 0.4390   |
| 0.852         | 35.0  | 210  | 1.1783          | 0.4634   |
| 0.852         | 36.0  | 216  | 1.2807          | 0.4878   |
| 0.8357        | 37.0  | 222  | 1.2879          | 0.4878   |
| 0.8357        | 38.0  | 228  | 1.3101          | 0.4390   |
| 0.7932        | 39.0  | 234  | 1.2773          | 0.4878   |
| 0.7254        | 40.0  | 240  | 1.3480          | 0.4878   |
| 0.7254        | 41.0  | 246  | 1.3839          | 0.4878   |
| 0.7183        | 42.0  | 252  | 1.3674          | 0.4878   |
| 0.7183        | 43.0  | 258  | 1.3674          | 0.4878   |
| 0.6348        | 44.0  | 264  | 1.3674          | 0.4878   |
| 0.6561        | 45.0  | 270  | 1.3674          | 0.4878   |
| 0.6561        | 46.0  | 276  | 1.3674          | 0.4878   |
| 0.6538        | 47.0  | 282  | 1.3674          | 0.4878   |
| 0.6538        | 48.0  | 288  | 1.3674          | 0.4878   |
| 0.6489        | 49.0  | 294  | 1.3674          | 0.4878   |
| 0.6536        | 50.0  | 300  | 1.3674          | 0.4878   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-base-patch16-224", "model-index": [{"name": "hushem_1x_deit_base_rms_001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.4878048780487805, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us