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# hushem_1x_deit_base_sgd_001_fold3

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: 1.3334
- Accuracy: 0.4186

## 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    | 1.3830          | 0.3721   |
| 1.4361        | 2.0   | 12   | 1.3798          | 0.3256   |
| 1.4361        | 3.0   | 18   | 1.3766          | 0.3256   |
| 1.4161        | 4.0   | 24   | 1.3738          | 0.3023   |
| 1.4308        | 5.0   | 30   | 1.3713          | 0.3256   |
| 1.4308        | 6.0   | 36   | 1.3692          | 0.3488   |
| 1.4008        | 7.0   | 42   | 1.3671          | 0.3721   |
| 1.4008        | 8.0   | 48   | 1.3650          | 0.3721   |
| 1.3927        | 9.0   | 54   | 1.3634          | 0.3721   |
| 1.37          | 10.0  | 60   | 1.3616          | 0.3721   |
| 1.37          | 11.0  | 66   | 1.3601          | 0.3953   |
| 1.3698        | 12.0  | 72   | 1.3586          | 0.3953   |
| 1.3698        | 13.0  | 78   | 1.3569          | 0.4419   |
| 1.3588        | 14.0  | 84   | 1.3553          | 0.4186   |
| 1.3582        | 15.0  | 90   | 1.3538          | 0.4186   |
| 1.3582        | 16.0  | 96   | 1.3522          | 0.4186   |
| 1.3505        | 17.0  | 102  | 1.3510          | 0.4186   |
| 1.3505        | 18.0  | 108  | 1.3496          | 0.4186   |
| 1.3337        | 19.0  | 114  | 1.3483          | 0.4186   |
| 1.3364        | 20.0  | 120  | 1.3470          | 0.4186   |
| 1.3364        | 21.0  | 126  | 1.3459          | 0.4186   |
| 1.3337        | 22.0  | 132  | 1.3449          | 0.4186   |
| 1.3337        | 23.0  | 138  | 1.3437          | 0.4186   |
| 1.3242        | 24.0  | 144  | 1.3426          | 0.3953   |
| 1.3247        | 25.0  | 150  | 1.3416          | 0.3953   |
| 1.3247        | 26.0  | 156  | 1.3407          | 0.3953   |
| 1.314         | 27.0  | 162  | 1.3398          | 0.3953   |
| 1.314         | 28.0  | 168  | 1.3390          | 0.3953   |
| 1.3132        | 29.0  | 174  | 1.3382          | 0.3953   |
| 1.3139        | 30.0  | 180  | 1.3375          | 0.3953   |
| 1.3139        | 31.0  | 186  | 1.3369          | 0.4186   |
| 1.3104        | 32.0  | 192  | 1.3363          | 0.3953   |
| 1.3104        | 33.0  | 198  | 1.3357          | 0.3953   |
| 1.3084        | 34.0  | 204  | 1.3352          | 0.3953   |
| 1.3046        | 35.0  | 210  | 1.3348          | 0.4186   |
| 1.3046        | 36.0  | 216  | 1.3345          | 0.4186   |
| 1.3016        | 37.0  | 222  | 1.3341          | 0.4186   |
| 1.3016        | 38.0  | 228  | 1.3339          | 0.4186   |
| 1.3084        | 39.0  | 234  | 1.3337          | 0.4186   |
| 1.3045        | 40.0  | 240  | 1.3335          | 0.4186   |
| 1.3045        | 41.0  | 246  | 1.3335          | 0.4186   |
| 1.2931        | 42.0  | 252  | 1.3334          | 0.4186   |
| 1.2931        | 43.0  | 258  | 1.3334          | 0.4186   |
| 1.3105        | 44.0  | 264  | 1.3334          | 0.4186   |
| 1.2967        | 45.0  | 270  | 1.3334          | 0.4186   |
| 1.2967        | 46.0  | 276  | 1.3334          | 0.4186   |
| 1.3024        | 47.0  | 282  | 1.3334          | 0.4186   |
| 1.3024        | 48.0  | 288  | 1.3334          | 0.4186   |
| 1.3038        | 49.0  | 294  | 1.3334          | 0.4186   |
| 1.3026        | 50.0  | 300  | 1.3334          | 0.4186   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- 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_sgd_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": 0.4186046511627907, "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