transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_base_rms_0001_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: 0.7555555555555555
---

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# hushem_40x_deit_base_rms_0001_fold2

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0887
- Accuracy: 0.7556

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0825        | 1.0   | 215   | 1.5281          | 0.7111   |
| 0.0311        | 2.0   | 430   | 1.2158          | 0.8      |
| 0.0011        | 3.0   | 645   | 1.8306          | 0.6889   |
| 0.0414        | 4.0   | 860   | 2.0416          | 0.7333   |
| 0.0002        | 5.0   | 1075  | 2.3340          | 0.6444   |
| 0.0027        | 6.0   | 1290  | 1.1579          | 0.7556   |
| 0.0001        | 7.0   | 1505  | 2.3412          | 0.6889   |
| 0.0           | 8.0   | 1720  | 2.3885          | 0.7111   |
| 0.0           | 9.0   | 1935  | 2.4917          | 0.7333   |
| 0.0           | 10.0  | 2150  | 2.6169          | 0.7333   |
| 0.0           | 11.0  | 2365  | 2.7660          | 0.7333   |
| 0.0           | 12.0  | 2580  | 2.9176          | 0.7333   |
| 0.0           | 13.0  | 2795  | 3.0652          | 0.7333   |
| 0.0           | 14.0  | 3010  | 3.1998          | 0.7556   |
| 0.0           | 15.0  | 3225  | 3.3068          | 0.7556   |
| 0.0           | 16.0  | 3440  | 3.4034          | 0.7556   |
| 0.0           | 17.0  | 3655  | 3.4958          | 0.7556   |
| 0.0           | 18.0  | 3870  | 3.5902          | 0.7556   |
| 0.0           | 19.0  | 4085  | 3.6748          | 0.7556   |
| 0.0           | 20.0  | 4300  | 3.7449          | 0.7556   |
| 0.0           | 21.0  | 4515  | 3.7990          | 0.7556   |
| 0.0           | 22.0  | 4730  | 3.8408          | 0.7556   |
| 0.0           | 23.0  | 4945  | 3.8743          | 0.7556   |
| 0.0           | 24.0  | 5160  | 3.9017          | 0.7556   |
| 0.0           | 25.0  | 5375  | 3.9247          | 0.7556   |
| 0.0           | 26.0  | 5590  | 3.9444          | 0.7556   |
| 0.0           | 27.0  | 5805  | 3.9616          | 0.7556   |
| 0.0           | 28.0  | 6020  | 3.9766          | 0.7556   |
| 0.0           | 29.0  | 6235  | 3.9899          | 0.7556   |
| 0.0           | 30.0  | 6450  | 4.0018          | 0.7556   |
| 0.0           | 31.0  | 6665  | 4.0124          | 0.7556   |
| 0.0           | 32.0  | 6880  | 4.0219          | 0.7556   |
| 0.0           | 33.0  | 7095  | 4.0305          | 0.7556   |
| 0.0           | 34.0  | 7310  | 4.0382          | 0.7556   |
| 0.0           | 35.0  | 7525  | 4.0452          | 0.7556   |
| 0.0           | 36.0  | 7740  | 4.0514          | 0.7556   |
| 0.0           | 37.0  | 7955  | 4.0571          | 0.7556   |
| 0.0           | 38.0  | 8170  | 4.0622          | 0.7556   |
| 0.0           | 39.0  | 8385  | 4.0668          | 0.7556   |
| 0.0           | 40.0  | 8600  | 4.0708          | 0.7556   |
| 0.0           | 41.0  | 8815  | 4.0744          | 0.7556   |
| 0.0           | 42.0  | 9030  | 4.0776          | 0.7556   |
| 0.0           | 43.0  | 9245  | 4.0803          | 0.7556   |
| 0.0           | 44.0  | 9460  | 4.0826          | 0.7556   |
| 0.0           | 45.0  | 9675  | 4.0846          | 0.7556   |
| 0.0           | 46.0  | 9890  | 4.0861          | 0.7556   |
| 0.0           | 47.0  | 10105 | 4.0873          | 0.7556   |
| 0.0           | 48.0  | 10320 | 4.0881          | 0.7556   |
| 0.0           | 49.0  | 10535 | 4.0886          | 0.7556   |
| 0.0           | 50.0  | 10750 | 4.0887          | 0.7556   |


### Framework versions

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