
<!-- 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_1x_deit_tiny_adamax_lr0001_fold3

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: 0.8641
- Accuracy: 0.6977

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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        | 0.67  | 1    | 1.6041          | 0.2558   |
| No log        | 2.0   | 3    | 1.2890          | 0.3953   |
| No log        | 2.67  | 4    | 1.2944          | 0.3023   |
| No log        | 4.0   | 6    | 1.2013          | 0.4186   |
| No log        | 4.67  | 7    | 1.1135          | 0.4186   |
| No log        | 6.0   | 9    | 1.0796          | 0.5349   |
| 1.2559        | 6.67  | 10   | 1.0570          | 0.5581   |
| 1.2559        | 8.0   | 12   | 1.1038          | 0.4884   |
| 1.2559        | 8.67  | 13   | 1.0764          | 0.4884   |
| 1.2559        | 10.0  | 15   | 0.9749          | 0.5349   |
| 1.2559        | 10.67 | 16   | 0.9354          | 0.5581   |
| 1.2559        | 12.0  | 18   | 0.9274          | 0.6279   |
| 1.2559        | 12.67 | 19   | 0.9435          | 0.6512   |
| 0.4315        | 14.0  | 21   | 0.9225          | 0.6512   |
| 0.4315        | 14.67 | 22   | 0.9168          | 0.6279   |
| 0.4315        | 16.0  | 24   | 0.8830          | 0.6279   |
| 0.4315        | 16.67 | 25   | 0.8956          | 0.6512   |
| 0.4315        | 18.0  | 27   | 0.9038          | 0.6744   |
| 0.4315        | 18.67 | 28   | 0.8913          | 0.6744   |
| 0.058         | 20.0  | 30   | 0.8683          | 0.6512   |
| 0.058         | 20.67 | 31   | 0.8553          | 0.6744   |
| 0.058         | 22.0  | 33   | 0.8508          | 0.6977   |
| 0.058         | 22.67 | 34   | 0.8546          | 0.6977   |
| 0.058         | 24.0  | 36   | 0.8627          | 0.6977   |
| 0.058         | 24.67 | 37   | 0.8639          | 0.6977   |
| 0.058         | 26.0  | 39   | 0.8636          | 0.7209   |
| 0.0086        | 26.67 | 40   | 0.8627          | 0.7209   |
| 0.0086        | 28.0  | 42   | 0.8622          | 0.7209   |
| 0.0086        | 28.67 | 43   | 0.8622          | 0.6977   |
| 0.0086        | 30.0  | 45   | 0.8629          | 0.6977   |
| 0.0086        | 30.67 | 46   | 0.8632          | 0.6977   |
| 0.0086        | 32.0  | 48   | 0.8638          | 0.6977   |
| 0.0086        | 32.67 | 49   | 0.8640          | 0.6977   |
| 0.004         | 33.33 | 50   | 0.8641          | 0.6977   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

01_normal 02_tapered 03_pyriform 04_amorphous