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# hushem_1x_deit_small_adamax_001_fold3

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: 3.7699
- Accuracy: 0.4651

## 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    | 1.4218          | 0.2558   |
| 1.7221        | 2.0   | 12   | 1.4061          | 0.3953   |
| 1.7221        | 3.0   | 18   | 1.4801          | 0.3256   |
| 1.2972        | 4.0   | 24   | 1.5453          | 0.3023   |
| 1.2115        | 5.0   | 30   | 1.2993          | 0.3953   |
| 1.2115        | 6.0   | 36   | 1.4486          | 0.3721   |
| 1.1196        | 7.0   | 42   | 1.4881          | 0.3721   |
| 1.1196        | 8.0   | 48   | 1.2031          | 0.4419   |
| 1.0394        | 9.0   | 54   | 1.1825          | 0.4651   |
| 0.9076        | 10.0  | 60   | 1.3831          | 0.3953   |
| 0.9076        | 11.0  | 66   | 1.5606          | 0.3953   |
| 0.8351        | 12.0  | 72   | 1.6879          | 0.3721   |
| 0.8351        | 13.0  | 78   | 1.5744          | 0.5581   |
| 0.7325        | 14.0  | 84   | 2.1220          | 0.5116   |
| 0.5767        | 15.0  | 90   | 2.2458          | 0.4884   |
| 0.5767        | 16.0  | 96   | 2.4745          | 0.3953   |
| 0.487         | 17.0  | 102  | 2.9255          | 0.3953   |
| 0.487         | 18.0  | 108  | 2.8169          | 0.4186   |
| 0.265         | 19.0  | 114  | 2.9600          | 0.4419   |
| 0.2739        | 20.0  | 120  | 3.0131          | 0.3953   |
| 0.2739        | 21.0  | 126  | 3.2413          | 0.4186   |
| 0.1684        | 22.0  | 132  | 4.9920          | 0.3953   |
| 0.1684        | 23.0  | 138  | 3.1514          | 0.5116   |
| 0.3265        | 24.0  | 144  | 4.1598          | 0.3953   |
| 0.2652        | 25.0  | 150  | 3.3248          | 0.4651   |
| 0.2652        | 26.0  | 156  | 3.1898          | 0.4884   |
| 0.1992        | 27.0  | 162  | 3.7937          | 0.3953   |
| 0.1992        | 28.0  | 168  | 3.9838          | 0.4884   |
| 0.1826        | 29.0  | 174  | 3.5764          | 0.3721   |
| 0.124         | 30.0  | 180  | 4.1231          | 0.4419   |
| 0.124         | 31.0  | 186  | 4.1455          | 0.4186   |
| 0.1353        | 32.0  | 192  | 3.9925          | 0.4186   |
| 0.1353        | 33.0  | 198  | 3.7016          | 0.5581   |
| 0.0743        | 34.0  | 204  | 3.7997          | 0.5349   |
| 0.0362        | 35.0  | 210  | 3.6073          | 0.4884   |
| 0.0362        | 36.0  | 216  | 3.6198          | 0.4651   |
| 0.0082        | 37.0  | 222  | 3.6509          | 0.4651   |
| 0.0082        | 38.0  | 228  | 3.7081          | 0.4651   |
| 0.003         | 39.0  | 234  | 3.7432          | 0.4651   |
| 0.002         | 40.0  | 240  | 3.7616          | 0.4651   |
| 0.002         | 41.0  | 246  | 3.7690          | 0.4651   |
| 0.0018        | 42.0  | 252  | 3.7699          | 0.4651   |
| 0.0018        | 43.0  | 258  | 3.7699          | 0.4651   |
| 0.0016        | 44.0  | 264  | 3.7699          | 0.4651   |
| 0.0017        | 45.0  | 270  | 3.7699          | 0.4651   |
| 0.0017        | 46.0  | 276  | 3.7699          | 0.4651   |
| 0.0017        | 47.0  | 282  | 3.7699          | 0.4651   |
| 0.0017        | 48.0  | 288  | 3.7699          | 0.4651   |
| 0.0018        | 49.0  | 294  | 3.7699          | 0.4651   |
| 0.0017        | 50.0  | 300  | 3.7699          | 0.4651   |


### 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-small-patch16-224", "model-index": [{"name": "hushem_1x_deit_small_adamax_001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.46511627906976744, "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