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# hushem_1x_deit_tiny_adamax_lr0001_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: 1.3365
- Accuracy: 0.5778

## 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    | 1.6054          | 0.2444   |
| No log        | 2.0   | 3    | 1.3436          | 0.3556   |
| No log        | 2.67  | 4    | 1.3392          | 0.2889   |
| No log        | 4.0   | 6    | 1.3661          | 0.2444   |
| No log        | 4.67  | 7    | 1.3117          | 0.3333   |
| No log        | 6.0   | 9    | 1.4031          | 0.2889   |
| 1.1803        | 6.67  | 10   | 1.2845          | 0.4222   |
| 1.1803        | 8.0   | 12   | 1.3559          | 0.3333   |
| 1.1803        | 8.67  | 13   | 1.3178          | 0.4      |
| 1.1803        | 10.0  | 15   | 1.1302          | 0.5778   |
| 1.1803        | 10.67 | 16   | 1.2145          | 0.5556   |
| 1.1803        | 12.0  | 18   | 1.3484          | 0.4      |
| 1.1803        | 12.67 | 19   | 1.1709          | 0.5333   |
| 0.3935        | 14.0  | 21   | 1.1495          | 0.5556   |
| 0.3935        | 14.67 | 22   | 1.2656          | 0.4889   |
| 0.3935        | 16.0  | 24   | 1.1929          | 0.5333   |
| 0.3935        | 16.67 | 25   | 1.1205          | 0.5556   |
| 0.3935        | 18.0  | 27   | 1.1729          | 0.5333   |
| 0.3935        | 18.67 | 28   | 1.2656          | 0.5111   |
| 0.0911        | 20.0  | 30   | 1.3172          | 0.5556   |
| 0.0911        | 20.67 | 31   | 1.2343          | 0.5556   |
| 0.0911        | 22.0  | 33   | 1.1439          | 0.6      |
| 0.0911        | 22.67 | 34   | 1.1167          | 0.6222   |
| 0.0911        | 24.0  | 36   | 1.1537          | 0.6      |
| 0.0911        | 24.67 | 37   | 1.2658          | 0.5778   |
| 0.0911        | 26.0  | 39   | 1.3705          | 0.5556   |
| 0.0269        | 26.67 | 40   | 1.3468          | 0.5778   |
| 0.0269        | 28.0  | 42   | 1.2914          | 0.6      |
| 0.0269        | 28.67 | 43   | 1.2807          | 0.6      |
| 0.0269        | 30.0  | 45   | 1.2833          | 0.6      |
| 0.0269        | 30.67 | 46   | 1.3004          | 0.5778   |
| 0.0269        | 32.0  | 48   | 1.3271          | 0.5778   |
| 0.0269        | 32.67 | 49   | 1.3342          | 0.5778   |
| 0.0102        | 33.33 | 50   | 1.3365          | 0.5778   |


### 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