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# hushem_5x_deit_tiny_adamax_0001_fold4

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: 0.5076
- Accuracy: 0.8571

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.876         | 1.0   | 28   | 0.7721          | 0.6667   |
| 0.2335        | 2.0   | 56   | 0.4611          | 0.8571   |
| 0.0719        | 3.0   | 84   | 0.6242          | 0.6905   |
| 0.0277        | 4.0   | 112  | 0.6528          | 0.7857   |
| 0.0032        | 5.0   | 140  | 0.4735          | 0.7857   |
| 0.0032        | 6.0   | 168  | 0.4579          | 0.8095   |
| 0.0006        | 7.0   | 196  | 0.5092          | 0.8333   |
| 0.0003        | 8.0   | 224  | 0.3894          | 0.8333   |
| 0.0002        | 9.0   | 252  | 0.4099          | 0.8810   |
| 0.0001        | 10.0  | 280  | 0.4092          | 0.8571   |
| 0.0001        | 11.0  | 308  | 0.4206          | 0.8571   |
| 0.0001        | 12.0  | 336  | 0.4259          | 0.8571   |
| 0.0001        | 13.0  | 364  | 0.4295          | 0.8571   |
| 0.0001        | 14.0  | 392  | 0.4367          | 0.8571   |
| 0.0001        | 15.0  | 420  | 0.4435          | 0.8571   |
| 0.0001        | 16.0  | 448  | 0.4513          | 0.8571   |
| 0.0001        | 17.0  | 476  | 0.4519          | 0.8571   |
| 0.0001        | 18.0  | 504  | 0.4534          | 0.8571   |
| 0.0001        | 19.0  | 532  | 0.4605          | 0.8571   |
| 0.0001        | 20.0  | 560  | 0.4613          | 0.8571   |
| 0.0001        | 21.0  | 588  | 0.4650          | 0.8571   |
| 0.0001        | 22.0  | 616  | 0.4689          | 0.8571   |
| 0.0001        | 23.0  | 644  | 0.4679          | 0.8571   |
| 0.0           | 24.0  | 672  | 0.4734          | 0.8571   |
| 0.0001        | 25.0  | 700  | 0.4768          | 0.8571   |
| 0.0           | 26.0  | 728  | 0.4779          | 0.8571   |
| 0.0001        | 27.0  | 756  | 0.4799          | 0.8571   |
| 0.0           | 28.0  | 784  | 0.4834          | 0.8571   |
| 0.0           | 29.0  | 812  | 0.4854          | 0.8571   |
| 0.0           | 30.0  | 840  | 0.4883          | 0.8571   |
| 0.0           | 31.0  | 868  | 0.4908          | 0.8571   |
| 0.0           | 32.0  | 896  | 0.4928          | 0.8571   |
| 0.0           | 33.0  | 924  | 0.4945          | 0.8571   |
| 0.0           | 34.0  | 952  | 0.4953          | 0.8571   |
| 0.0           | 35.0  | 980  | 0.4954          | 0.8571   |
| 0.0           | 36.0  | 1008 | 0.4965          | 0.8571   |
| 0.0           | 37.0  | 1036 | 0.4980          | 0.8571   |
| 0.0           | 38.0  | 1064 | 0.4998          | 0.8571   |
| 0.0           | 39.0  | 1092 | 0.5007          | 0.8571   |
| 0.0           | 40.0  | 1120 | 0.5020          | 0.8571   |
| 0.0           | 41.0  | 1148 | 0.5023          | 0.8571   |
| 0.0           | 42.0  | 1176 | 0.5029          | 0.8571   |
| 0.0           | 43.0  | 1204 | 0.5047          | 0.8571   |
| 0.0           | 44.0  | 1232 | 0.5059          | 0.8571   |
| 0.0           | 45.0  | 1260 | 0.5064          | 0.8571   |
| 0.0           | 46.0  | 1288 | 0.5070          | 0.8571   |
| 0.0           | 47.0  | 1316 | 0.5074          | 0.8571   |
| 0.0           | 48.0  | 1344 | 0.5076          | 0.8571   |
| 0.0           | 49.0  | 1372 | 0.5076          | 0.8571   |
| 0.0           | 50.0  | 1400 | 0.5076          | 0.8571   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "hushem_5x_deit_tiny_adamax_0001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8571428571428571, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors 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