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# hushem_40x_deit_tiny_sgd_001_fold1

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: 0.9268
- Accuracy: 0.7333

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1534        | 1.0   | 215   | 1.3121          | 0.3778   |
| 0.8744        | 2.0   | 430   | 1.2305          | 0.5111   |
| 0.7578        | 3.0   | 645   | 1.1023          | 0.5556   |
| 0.6354        | 4.0   | 860   | 0.9584          | 0.5778   |
| 0.4832        | 5.0   | 1075  | 0.8877          | 0.6444   |
| 0.4506        | 6.0   | 1290  | 0.8214          | 0.6889   |
| 0.3619        | 7.0   | 1505  | 0.8077          | 0.6889   |
| 0.3187        | 8.0   | 1720  | 0.7845          | 0.6667   |
| 0.2423        | 9.0   | 1935  | 0.7629          | 0.7111   |
| 0.2351        | 10.0  | 2150  | 0.7464          | 0.7333   |
| 0.2043        | 11.0  | 2365  | 0.7249          | 0.6889   |
| 0.1712        | 12.0  | 2580  | 0.7297          | 0.7111   |
| 0.1294        | 13.0  | 2795  | 0.7280          | 0.7333   |
| 0.1185        | 14.0  | 3010  | 0.7610          | 0.7333   |
| 0.1264        | 15.0  | 3225  | 0.7479          | 0.7333   |
| 0.0869        | 16.0  | 3440  | 0.7617          | 0.7333   |
| 0.0902        | 17.0  | 3655  | 0.7623          | 0.7333   |
| 0.0782        | 18.0  | 3870  | 0.7805          | 0.7333   |
| 0.071         | 19.0  | 4085  | 0.7715          | 0.7333   |
| 0.063         | 20.0  | 4300  | 0.7777          | 0.7333   |
| 0.0587        | 21.0  | 4515  | 0.7497          | 0.7333   |
| 0.0675        | 22.0  | 4730  | 0.7998          | 0.7333   |
| 0.0426        | 23.0  | 4945  | 0.8200          | 0.7333   |
| 0.0373        | 24.0  | 5160  | 0.8281          | 0.7111   |
| 0.0441        | 25.0  | 5375  | 0.8317          | 0.7111   |
| 0.0323        | 26.0  | 5590  | 0.8133          | 0.7111   |
| 0.0359        | 27.0  | 5805  | 0.8214          | 0.7111   |
| 0.0291        | 28.0  | 6020  | 0.8265          | 0.7111   |
| 0.0287        | 29.0  | 6235  | 0.8490          | 0.7111   |
| 0.0271        | 30.0  | 6450  | 0.8534          | 0.7111   |
| 0.0256        | 31.0  | 6665  | 0.8626          | 0.7111   |
| 0.0212        | 32.0  | 6880  | 0.8791          | 0.7111   |
| 0.0155        | 33.0  | 7095  | 0.8740          | 0.7333   |
| 0.0144        | 34.0  | 7310  | 0.8433          | 0.7333   |
| 0.0132        | 35.0  | 7525  | 0.8680          | 0.7333   |
| 0.015         | 36.0  | 7740  | 0.8880          | 0.7333   |
| 0.0129        | 37.0  | 7955  | 0.8931          | 0.7333   |
| 0.018         | 38.0  | 8170  | 0.8891          | 0.7333   |
| 0.0092        | 39.0  | 8385  | 0.9122          | 0.7333   |
| 0.0085        | 40.0  | 8600  | 0.9159          | 0.7333   |
| 0.0124        | 41.0  | 8815  | 0.9199          | 0.7333   |
| 0.0125        | 42.0  | 9030  | 0.9056          | 0.7333   |
| 0.0107        | 43.0  | 9245  | 0.9191          | 0.7333   |
| 0.0095        | 44.0  | 9460  | 0.9083          | 0.7333   |
| 0.0115        | 45.0  | 9675  | 0.9189          | 0.7333   |
| 0.0088        | 46.0  | 9890  | 0.9241          | 0.7333   |
| 0.0065        | 47.0  | 10105 | 0.9299          | 0.7333   |
| 0.007         | 48.0  | 10320 | 0.9257          | 0.7333   |
| 0.0129        | 49.0  | 10535 | 0.9260          | 0.7333   |
| 0.0229        | 50.0  | 10750 | 0.9268          | 0.7333   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7333333333333333, "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