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# hushem_40x_deit_tiny_sgd_001_fold5

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5908
- Accuracy: 0.8293

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1602        | 1.0   | 220   | 1.4008          | 0.2927   |
| 0.8954        | 2.0   | 440   | 1.2274          | 0.3902   |
| 0.7859        | 3.0   | 660   | 1.0703          | 0.5366   |
| 0.6718        | 4.0   | 880   | 0.9455          | 0.6098   |
| 0.5505        | 5.0   | 1100  | 0.8399          | 0.6341   |
| 0.4372        | 6.0   | 1320  | 0.7728          | 0.7073   |
| 0.3616        | 7.0   | 1540  | 0.7172          | 0.7317   |
| 0.291         | 8.0   | 1760  | 0.7018          | 0.7317   |
| 0.2597        | 9.0   | 1980  | 0.6678          | 0.7317   |
| 0.2339        | 10.0  | 2200  | 0.6575          | 0.7073   |
| 0.2227        | 11.0  | 2420  | 0.6389          | 0.7073   |
| 0.179         | 12.0  | 2640  | 0.6500          | 0.7073   |
| 0.1598        | 13.0  | 2860  | 0.6290          | 0.7073   |
| 0.1448        | 14.0  | 3080  | 0.6491          | 0.6585   |
| 0.1209        | 15.0  | 3300  | 0.6174          | 0.7073   |
| 0.1192        | 16.0  | 3520  | 0.6084          | 0.7073   |
| 0.1037        | 17.0  | 3740  | 0.6013          | 0.7317   |
| 0.0848        | 18.0  | 3960  | 0.5985          | 0.7073   |
| 0.1048        | 19.0  | 4180  | 0.5896          | 0.7317   |
| 0.0665        | 20.0  | 4400  | 0.6043          | 0.7073   |
| 0.0723        | 21.0  | 4620  | 0.5932          | 0.7561   |
| 0.0444        | 22.0  | 4840  | 0.5749          | 0.8049   |
| 0.0448        | 23.0  | 5060  | 0.5862          | 0.7805   |
| 0.0396        | 24.0  | 5280  | 0.5758          | 0.8049   |
| 0.0378        | 25.0  | 5500  | 0.5566          | 0.8293   |
| 0.0428        | 26.0  | 5720  | 0.5740          | 0.8293   |
| 0.0345        | 27.0  | 5940  | 0.5631          | 0.8049   |
| 0.0515        | 28.0  | 6160  | 0.5844          | 0.8049   |
| 0.0324        | 29.0  | 6380  | 0.5872          | 0.8293   |
| 0.0292        | 30.0  | 6600  | 0.5789          | 0.8293   |
| 0.0208        | 31.0  | 6820  | 0.5688          | 0.8293   |
| 0.0421        | 32.0  | 7040  | 0.5703          | 0.8293   |
| 0.0246        | 33.0  | 7260  | 0.5663          | 0.8293   |
| 0.0318        | 34.0  | 7480  | 0.5726          | 0.8293   |
| 0.0151        | 35.0  | 7700  | 0.5751          | 0.8293   |
| 0.0169        | 36.0  | 7920  | 0.5772          | 0.8293   |
| 0.017         | 37.0  | 8140  | 0.5665          | 0.8293   |
| 0.0393        | 38.0  | 8360  | 0.5815          | 0.8293   |
| 0.0218        | 39.0  | 8580  | 0.5765          | 0.8293   |
| 0.0156        | 40.0  | 8800  | 0.5742          | 0.8293   |
| 0.0183        | 41.0  | 9020  | 0.5956          | 0.8293   |
| 0.0155        | 42.0  | 9240  | 0.5886          | 0.8293   |
| 0.0134        | 43.0  | 9460  | 0.5775          | 0.8293   |
| 0.0186        | 44.0  | 9680  | 0.5921          | 0.8293   |
| 0.0177        | 45.0  | 9900  | 0.5863          | 0.8293   |
| 0.0115        | 46.0  | 10120 | 0.5918          | 0.8293   |
| 0.0196        | 47.0  | 10340 | 0.5892          | 0.8293   |
| 0.0172        | 48.0  | 10560 | 0.5892          | 0.8293   |
| 0.0129        | 49.0  | 10780 | 0.5910          | 0.8293   |
| 0.0197        | 50.0  | 11000 | 0.5908          | 0.8293   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+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-tiny-patch16-224", "model-index": [{"name": "hushem_40x_deit_tiny_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": 0.8292682926829268, "name": "Accuracy"}]}]}]}
transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us