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# hushem_40x_deit_base_rms_0001_fold1

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: 2.4716
- Accuracy: 0.8222

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0732        | 1.0   | 215   | 0.6365          | 0.7556   |
| 0.102         | 2.0   | 430   | 1.5996          | 0.6889   |
| 0.0272        | 3.0   | 645   | 0.8191          | 0.8      |
| 0.0001        | 4.0   | 860   | 0.8601          | 0.8      |
| 0.1057        | 5.0   | 1075  | 0.9797          | 0.7778   |
| 0.0863        | 6.0   | 1290  | 1.8140          | 0.6889   |
| 0.0131        | 7.0   | 1505  | 1.1217          | 0.8      |
| 0.0           | 8.0   | 1720  | 1.2704          | 0.8      |
| 0.0           | 9.0   | 1935  | 1.3271          | 0.8222   |
| 0.0           | 10.0  | 2150  | 1.4318          | 0.8222   |
| 0.0           | 11.0  | 2365  | 1.5412          | 0.7778   |
| 0.0           | 12.0  | 2580  | 1.6553          | 0.8      |
| 0.0           | 13.0  | 2795  | 1.7666          | 0.8      |
| 0.0           | 14.0  | 3010  | 1.8788          | 0.8444   |
| 0.0           | 15.0  | 3225  | 1.9590          | 0.8444   |
| 0.0           | 16.0  | 3440  | 2.0334          | 0.8444   |
| 0.0           | 17.0  | 3655  | 2.0934          | 0.8444   |
| 0.0           | 18.0  | 3870  | 2.1509          | 0.8444   |
| 0.0           | 19.0  | 4085  | 2.2044          | 0.8444   |
| 0.0           | 20.0  | 4300  | 2.2497          | 0.8444   |
| 0.0           | 21.0  | 4515  | 2.2856          | 0.8444   |
| 0.0           | 22.0  | 4730  | 2.3133          | 0.8444   |
| 0.0           | 23.0  | 4945  | 2.3351          | 0.8444   |
| 0.0           | 24.0  | 5160  | 2.3530          | 0.8444   |
| 0.0           | 25.0  | 5375  | 2.3678          | 0.8444   |
| 0.0           | 26.0  | 5590  | 2.3804          | 0.8444   |
| 0.0           | 27.0  | 5805  | 2.3914          | 0.8444   |
| 0.0           | 28.0  | 6020  | 2.4010          | 0.8222   |
| 0.0           | 29.0  | 6235  | 2.4094          | 0.8222   |
| 0.0           | 30.0  | 6450  | 2.4170          | 0.8222   |
| 0.0           | 31.0  | 6665  | 2.4237          | 0.8222   |
| 0.0           | 32.0  | 6880  | 2.4297          | 0.8222   |
| 0.0           | 33.0  | 7095  | 2.4351          | 0.8222   |
| 0.0           | 34.0  | 7310  | 2.4400          | 0.8222   |
| 0.0           | 35.0  | 7525  | 2.4444          | 0.8222   |
| 0.0           | 36.0  | 7740  | 2.4484          | 0.8222   |
| 0.0           | 37.0  | 7955  | 2.4519          | 0.8222   |
| 0.0           | 38.0  | 8170  | 2.4551          | 0.8222   |
| 0.0           | 39.0  | 8385  | 2.4580          | 0.8222   |
| 0.0           | 40.0  | 8600  | 2.4605          | 0.8222   |
| 0.0           | 41.0  | 8815  | 2.4628          | 0.8222   |
| 0.0           | 42.0  | 9030  | 2.4647          | 0.8222   |
| 0.0           | 43.0  | 9245  | 2.4664          | 0.8222   |
| 0.0           | 44.0  | 9460  | 2.4679          | 0.8222   |
| 0.0           | 45.0  | 9675  | 2.4691          | 0.8222   |
| 0.0           | 46.0  | 9890  | 2.4700          | 0.8222   |
| 0.0           | 47.0  | 10105 | 2.4708          | 0.8222   |
| 0.0           | 48.0  | 10320 | 2.4713          | 0.8222   |
| 0.0           | 49.0  | 10535 | 2.4716          | 0.8222   |
| 0.0           | 50.0  | 10750 | 2.4716          | 0.8222   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+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-base-patch16-224", "model-index": [{"name": "hushem_40x_deit_base_rms_0001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8222222222222222, "name": "Accuracy"}]}]}]}
transformers pytorch 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