
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_40x_deit_small_sgd_001_fold5

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: 0.3138
- Accuracy: 0.8537

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2269        | 1.0   | 220   | 1.3889          | 0.3171   |
| 0.9985        | 2.0   | 440   | 1.1915          | 0.3902   |
| 0.8593        | 3.0   | 660   | 1.0700          | 0.5366   |
| 0.7571        | 4.0   | 880   | 0.9669          | 0.5854   |
| 0.6777        | 5.0   | 1100  | 0.8606          | 0.6341   |
| 0.5274        | 6.0   | 1320  | 0.7627          | 0.6585   |
| 0.4414        | 7.0   | 1540  | 0.6648          | 0.7317   |
| 0.4175        | 8.0   | 1760  | 0.6018          | 0.7805   |
| 0.316         | 9.0   | 1980  | 0.5359          | 0.7805   |
| 0.2588        | 10.0  | 2200  | 0.4774          | 0.8049   |
| 0.2327        | 11.0  | 2420  | 0.4274          | 0.8537   |
| 0.1962        | 12.0  | 2640  | 0.3959          | 0.8293   |
| 0.1844        | 13.0  | 2860  | 0.3504          | 0.8293   |
| 0.1541        | 14.0  | 3080  | 0.3380          | 0.8293   |
| 0.1252        | 15.0  | 3300  | 0.3134          | 0.8293   |
| 0.1083        | 16.0  | 3520  | 0.2915          | 0.8537   |
| 0.0934        | 17.0  | 3740  | 0.2801          | 0.8537   |
| 0.092         | 18.0  | 3960  | 0.2741          | 0.8780   |
| 0.083         | 19.0  | 4180  | 0.2729          | 0.8780   |
| 0.0654        | 20.0  | 4400  | 0.2600          | 0.8780   |
| 0.0561        | 21.0  | 4620  | 0.2597          | 0.8780   |
| 0.0451        | 22.0  | 4840  | 0.2669          | 0.8780   |
| 0.0472        | 23.0  | 5060  | 0.2513          | 0.8780   |
| 0.0354        | 24.0  | 5280  | 0.2691          | 0.8780   |
| 0.0367        | 25.0  | 5500  | 0.2575          | 0.8780   |
| 0.0263        | 26.0  | 5720  | 0.2498          | 0.8780   |
| 0.0333        | 27.0  | 5940  | 0.2592          | 0.8780   |
| 0.0309        | 28.0  | 6160  | 0.2598          | 0.8780   |
| 0.0217        | 29.0  | 6380  | 0.2806          | 0.8780   |
| 0.0156        | 30.0  | 6600  | 0.2646          | 0.8780   |
| 0.0138        | 31.0  | 6820  | 0.2633          | 0.8780   |
| 0.0242        | 32.0  | 7040  | 0.2880          | 0.8780   |
| 0.0128        | 33.0  | 7260  | 0.2733          | 0.8780   |
| 0.0109        | 34.0  | 7480  | 0.2902          | 0.8780   |
| 0.011         | 35.0  | 7700  | 0.2855          | 0.8780   |
| 0.0099        | 36.0  | 7920  | 0.3131          | 0.8537   |
| 0.0084        | 37.0  | 8140  | 0.2898          | 0.8780   |
| 0.0211        | 38.0  | 8360  | 0.3199          | 0.8537   |
| 0.014         | 39.0  | 8580  | 0.3071          | 0.8537   |
| 0.0076        | 40.0  | 8800  | 0.2872          | 0.8780   |
| 0.0086        | 41.0  | 9020  | 0.3095          | 0.8537   |
| 0.0068        | 42.0  | 9240  | 0.3068          | 0.8537   |
| 0.0085        | 43.0  | 9460  | 0.3042          | 0.8537   |
| 0.0079        | 44.0  | 9680  | 0.3170          | 0.8537   |
| 0.0089        | 45.0  | 9900  | 0.3144          | 0.8537   |
| 0.005         | 46.0  | 10120 | 0.3132          | 0.8537   |
| 0.0073        | 47.0  | 10340 | 0.3173          | 0.8537   |
| 0.01          | 48.0  | 10560 | 0.3150          | 0.8537   |
| 0.0068        | 49.0  | 10780 | 0.3144          | 0.8537   |
| 0.0068        | 50.0  | 11000 | 0.3138          | 0.8537   |


### 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-small-patch16-224", "model-index": [{"name": "hushem_40x_deit_small_sgd_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": 0.8536585365853658, "name": "Accuracy"}]}]}]}
transformers pytorch 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