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# hushem_1x_deit_base_rms_001_fold2

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: 1.0357
- Accuracy: 0.6444

## 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    | 5.4375          | 0.2667   |
| 5.152         | 2.0   | 12   | 2.4176          | 0.2444   |
| 5.152         | 3.0   | 18   | 1.6834          | 0.2444   |
| 2.2029        | 4.0   | 24   | 1.5993          | 0.2667   |
| 1.6431        | 5.0   | 30   | 1.5694          | 0.2444   |
| 1.6431        | 6.0   | 36   | 1.6003          | 0.2444   |
| 1.5667        | 7.0   | 42   | 1.5690          | 0.2444   |
| 1.5667        | 8.0   | 48   | 1.5571          | 0.2444   |
| 1.5065        | 9.0   | 54   | 1.4670          | 0.2444   |
| 1.4556        | 10.0  | 60   | 1.4809          | 0.2444   |
| 1.4556        | 11.0  | 66   | 1.4913          | 0.2667   |
| 1.4366        | 12.0  | 72   | 1.4381          | 0.2444   |
| 1.4366        | 13.0  | 78   | 1.5011          | 0.2667   |
| 1.45          | 14.0  | 84   | 1.6192          | 0.2667   |
| 1.6105        | 15.0  | 90   | 1.3933          | 0.2667   |
| 1.6105        | 16.0  | 96   | 1.3754          | 0.3556   |
| 1.463         | 17.0  | 102  | 1.6119          | 0.2444   |
| 1.463         | 18.0  | 108  | 1.4972          | 0.2444   |
| 1.4133        | 19.0  | 114  | 1.2907          | 0.3111   |
| 1.3552        | 20.0  | 120  | 1.3783          | 0.2667   |
| 1.3552        | 21.0  | 126  | 1.2531          | 0.4      |
| 1.2635        | 22.0  | 132  | 1.2107          | 0.4222   |
| 1.2635        | 23.0  | 138  | 1.2781          | 0.3778   |
| 1.2442        | 24.0  | 144  | 1.1028          | 0.4222   |
| 1.1223        | 25.0  | 150  | 1.1738          | 0.4444   |
| 1.1223        | 26.0  | 156  | 1.1566          | 0.5111   |
| 1.0131        | 27.0  | 162  | 1.0937          | 0.5111   |
| 1.0131        | 28.0  | 168  | 1.0849          | 0.5556   |
| 0.9912        | 29.0  | 174  | 1.3429          | 0.5111   |
| 0.853         | 30.0  | 180  | 0.9919          | 0.6222   |
| 0.853         | 31.0  | 186  | 1.0799          | 0.5556   |
| 0.6912        | 32.0  | 192  | 1.1042          | 0.5333   |
| 0.6912        | 33.0  | 198  | 1.0782          | 0.5556   |
| 0.6669        | 34.0  | 204  | 0.9785          | 0.5333   |
| 0.5453        | 35.0  | 210  | 1.1312          | 0.6444   |
| 0.5453        | 36.0  | 216  | 1.0910          | 0.5556   |
| 0.5668        | 37.0  | 222  | 1.1103          | 0.6      |
| 0.5668        | 38.0  | 228  | 1.1358          | 0.5778   |
| 0.4266        | 39.0  | 234  | 1.0340          | 0.6222   |
| 0.471         | 40.0  | 240  | 1.0428          | 0.6222   |
| 0.471         | 41.0  | 246  | 1.0358          | 0.6444   |
| 0.4178        | 42.0  | 252  | 1.0357          | 0.6444   |
| 0.4178        | 43.0  | 258  | 1.0357          | 0.6444   |
| 0.3636        | 44.0  | 264  | 1.0357          | 0.6444   |
| 0.3974        | 45.0  | 270  | 1.0357          | 0.6444   |
| 0.3974        | 46.0  | 276  | 1.0357          | 0.6444   |
| 0.3949        | 47.0  | 282  | 1.0357          | 0.6444   |
| 0.3949        | 48.0  | 288  | 1.0357          | 0.6444   |
| 0.3754        | 49.0  | 294  | 1.0357          | 0.6444   |
| 0.3739        | 50.0  | 300  | 1.0357          | 0.6444   |


### 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_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6444444444444445, "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