---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_tiny_rms_00001_fold2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6888888888888889
---

<!-- 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_40x_deit_tiny_rms_00001_fold2

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: 2.3474
- Accuracy: 0.6889

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0591        | 1.0   | 215   | 0.9478          | 0.7111   |
| 0.0016        | 2.0   | 430   | 1.0737          | 0.6889   |
| 0.0003        | 3.0   | 645   | 1.0732          | 0.7111   |
| 0.0001        | 4.0   | 860   | 1.2338          | 0.7111   |
| 0.0           | 5.0   | 1075  | 1.3886          | 0.7111   |
| 0.0           | 6.0   | 1290  | 1.5328          | 0.6889   |
| 0.0           | 7.0   | 1505  | 1.6761          | 0.6889   |
| 0.0           | 8.0   | 1720  | 1.8802          | 0.6889   |
| 0.0           | 9.0   | 1935  | 2.1375          | 0.6889   |
| 0.0           | 10.0  | 2150  | 2.2804          | 0.6889   |
| 0.0           | 11.0  | 2365  | 2.5018          | 0.6667   |
| 0.0           | 12.0  | 2580  | 2.6034          | 0.7111   |
| 0.0           | 13.0  | 2795  | 2.1119          | 0.7556   |
| 0.0           | 14.0  | 3010  | 2.5118          | 0.7111   |
| 0.0           | 15.0  | 3225  | 2.4215          | 0.6889   |
| 0.0           | 16.0  | 3440  | 2.4416          | 0.6889   |
| 0.0           | 17.0  | 3655  | 2.4789          | 0.6889   |
| 0.0           | 18.0  | 3870  | 2.5530          | 0.6889   |
| 0.0           | 19.0  | 4085  | 2.6223          | 0.6889   |
| 0.0           | 20.0  | 4300  | 2.7198          | 0.6889   |
| 0.0           | 21.0  | 4515  | 2.8171          | 0.7111   |
| 0.0           | 22.0  | 4730  | 2.8585          | 0.7111   |
| 0.0           | 23.0  | 4945  | 2.8584          | 0.7111   |
| 0.0           | 24.0  | 5160  | 2.7240          | 0.7111   |
| 0.0           | 25.0  | 5375  | 2.6522          | 0.7111   |
| 0.0           | 26.0  | 5590  | 2.6766          | 0.7111   |
| 0.0           | 27.0  | 5805  | 2.6051          | 0.7333   |
| 0.0           | 28.0  | 6020  | 2.4780          | 0.7333   |
| 0.0           | 29.0  | 6235  | 2.4371          | 0.7333   |
| 0.0           | 30.0  | 6450  | 2.3680          | 0.7333   |
| 0.0           | 31.0  | 6665  | 2.3696          | 0.7111   |
| 0.0           | 32.0  | 6880  | 2.3638          | 0.7333   |
| 0.0           | 33.0  | 7095  | 2.3261          | 0.7333   |
| 0.0           | 34.0  | 7310  | 2.3611          | 0.7333   |
| 0.0           | 35.0  | 7525  | 2.3737          | 0.7333   |
| 0.0           | 36.0  | 7740  | 2.3371          | 0.6889   |
| 0.0           | 37.0  | 7955  | 2.3450          | 0.7111   |
| 0.0           | 38.0  | 8170  | 2.3727          | 0.6889   |
| 0.0           | 39.0  | 8385  | 2.3620          | 0.6889   |
| 0.0           | 40.0  | 8600  | 2.3928          | 0.6889   |
| 0.0           | 41.0  | 8815  | 2.3547          | 0.6889   |
| 0.0           | 42.0  | 9030  | 2.3935          | 0.6889   |
| 0.0           | 43.0  | 9245  | 2.3835          | 0.6889   |
| 0.0           | 44.0  | 9460  | 2.3407          | 0.6889   |
| 0.0           | 45.0  | 9675  | 2.3628          | 0.6889   |
| 0.0           | 46.0  | 9890  | 2.3464          | 0.6889   |
| 0.0           | 47.0  | 10105 | 2.3571          | 0.6889   |
| 0.0           | 48.0  | 10320 | 2.3604          | 0.6889   |
| 0.0           | 49.0  | 10535 | 2.3495          | 0.6889   |
| 0.0           | 50.0  | 10750 | 2.3474          | 0.6889   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2