transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_rms_00001_fold1
  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: 0.8666666666666667
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hushem_40x_deit_small_rms_00001_fold1

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9061
- Accuracy: 0.8667

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0132        | 1.0   | 215   | 0.4686          | 0.8444   |
| 0.0004        | 2.0   | 430   | 0.6106          | 0.8222   |
| 0.0016        | 3.0   | 645   | 0.7608          | 0.8      |
| 0.0           | 4.0   | 860   | 0.5588          | 0.8667   |
| 0.0           | 5.0   | 1075  | 0.5395          | 0.8667   |
| 0.0           | 6.0   | 1290  | 0.5368          | 0.8889   |
| 0.0           | 7.0   | 1505  | 0.5575          | 0.8889   |
| 0.0           | 8.0   | 1720  | 0.5516          | 0.9111   |
| 0.0           | 9.0   | 1935  | 0.5817          | 0.9111   |
| 0.0           | 10.0  | 2150  | 0.5914          | 0.8667   |
| 0.0           | 11.0  | 2365  | 0.6168          | 0.8667   |
| 0.0           | 12.0  | 2580  | 0.7197          | 0.8667   |
| 0.0           | 13.0  | 2795  | 0.7066          | 0.8667   |
| 0.0           | 14.0  | 3010  | 0.7905          | 0.8667   |
| 0.0           | 15.0  | 3225  | 0.8099          | 0.8667   |
| 0.0           | 16.0  | 3440  | 0.9402          | 0.8444   |
| 0.0           | 17.0  | 3655  | 0.9239          | 0.8667   |
| 0.0           | 18.0  | 3870  | 0.9014          | 0.8444   |
| 0.0           | 19.0  | 4085  | 0.9346          | 0.8667   |
| 0.0           | 20.0  | 4300  | 0.8551          | 0.8667   |
| 0.0           | 21.0  | 4515  | 0.8933          | 0.8667   |
| 0.0           | 22.0  | 4730  | 0.9137          | 0.8667   |
| 0.0           | 23.0  | 4945  | 0.9179          | 0.8667   |
| 0.0           | 24.0  | 5160  | 0.8411          | 0.8667   |
| 0.0           | 25.0  | 5375  | 0.9276          | 0.8667   |
| 0.0           | 26.0  | 5590  | 0.9081          | 0.8667   |
| 0.0           | 27.0  | 5805  | 0.9378          | 0.8667   |
| 0.0           | 28.0  | 6020  | 0.9015          | 0.8667   |
| 0.0           | 29.0  | 6235  | 0.8989          | 0.8667   |
| 0.0           | 30.0  | 6450  | 0.9223          | 0.8667   |
| 0.0           | 31.0  | 6665  | 0.9424          | 0.8667   |
| 0.0           | 32.0  | 6880  | 0.9057          | 0.8667   |
| 0.0           | 33.0  | 7095  | 0.8894          | 0.8667   |
| 0.0           | 34.0  | 7310  | 0.9300          | 0.8667   |
| 0.0           | 35.0  | 7525  | 0.9491          | 0.8667   |
| 0.0           | 36.0  | 7740  | 0.8980          | 0.8667   |
| 0.0           | 37.0  | 7955  | 0.8706          | 0.8667   |
| 0.0           | 38.0  | 8170  | 0.8943          | 0.8667   |
| 0.0           | 39.0  | 8385  | 0.9073          | 0.8667   |
| 0.0           | 40.0  | 8600  | 0.9075          | 0.8667   |
| 0.0           | 41.0  | 8815  | 0.9113          | 0.8667   |
| 0.0           | 42.0  | 9030  | 0.9138          | 0.8667   |
| 0.0           | 43.0  | 9245  | 0.9218          | 0.8667   |
| 0.0           | 44.0  | 9460  | 0.9089          | 0.8667   |
| 0.0           | 45.0  | 9675  | 0.9120          | 0.8667   |
| 0.0           | 46.0  | 9890  | 0.9019          | 0.8667   |
| 0.0           | 47.0  | 10105 | 0.9058          | 0.8667   |
| 0.0           | 48.0  | 10320 | 0.9063          | 0.8667   |
| 0.0           | 49.0  | 10535 | 0.9035          | 0.8667   |
| 0.0           | 50.0  | 10750 | 0.9061          | 0.8667   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
