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_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: 0.7777777777777778
---

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# hushem_40x_deit_base_rms_00001_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: 2.2145
- Accuracy: 0.7778

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0124        | 1.0   | 215   | 0.9769          | 0.7556   |
| 0.0003        | 2.0   | 430   | 1.1164          | 0.7556   |
| 0.0001        | 3.0   | 645   | 1.2999          | 0.7556   |
| 0.0           | 4.0   | 860   | 1.4171          | 0.7556   |
| 0.0           | 5.0   | 1075  | 1.5668          | 0.7778   |
| 0.0           | 6.0   | 1290  | 1.6850          | 0.7778   |
| 0.0           | 7.0   | 1505  | 1.8146          | 0.7778   |
| 0.0           | 8.0   | 1720  | 1.9589          | 0.7778   |
| 0.0           | 9.0   | 1935  | 2.1064          | 0.8      |
| 0.0           | 10.0  | 2150  | 2.2093          | 0.8      |
| 0.0           | 11.0  | 2365  | 2.2933          | 0.8      |
| 0.0           | 12.0  | 2580  | 2.3766          | 0.8      |
| 0.0           | 13.0  | 2795  | 2.4083          | 0.7778   |
| 0.0           | 14.0  | 3010  | 2.4352          | 0.7778   |
| 0.0           | 15.0  | 3225  | 2.4429          | 0.7778   |
| 0.0           | 16.0  | 3440  | 2.4405          | 0.7778   |
| 0.0           | 17.0  | 3655  | 2.4464          | 0.7778   |
| 0.0           | 18.0  | 3870  | 2.4337          | 0.7778   |
| 0.0           | 19.0  | 4085  | 2.4439          | 0.7778   |
| 0.0           | 20.0  | 4300  | 2.4205          | 0.7778   |
| 0.0           | 21.0  | 4515  | 2.4211          | 0.7778   |
| 0.0           | 22.0  | 4730  | 2.4042          | 0.7778   |
| 0.0           | 23.0  | 4945  | 2.3825          | 0.7778   |
| 0.0           | 24.0  | 5160  | 2.3776          | 0.7778   |
| 0.0           | 25.0  | 5375  | 2.3705          | 0.7778   |
| 0.0           | 26.0  | 5590  | 2.3563          | 0.7778   |
| 0.0           | 27.0  | 5805  | 2.3321          | 0.7778   |
| 0.0           | 28.0  | 6020  | 2.3284          | 0.7778   |
| 0.0           | 29.0  | 6235  | 2.3256          | 0.7778   |
| 0.0           | 30.0  | 6450  | 2.3054          | 0.7778   |
| 0.0           | 31.0  | 6665  | 2.2910          | 0.7778   |
| 0.0           | 32.0  | 6880  | 2.2963          | 0.7778   |
| 0.0           | 33.0  | 7095  | 2.2902          | 0.7778   |
| 0.0           | 34.0  | 7310  | 2.2745          | 0.7778   |
| 0.0           | 35.0  | 7525  | 2.2617          | 0.7778   |
| 0.0           | 36.0  | 7740  | 2.2546          | 0.7778   |
| 0.0           | 37.0  | 7955  | 2.2630          | 0.7778   |
| 0.0           | 38.0  | 8170  | 2.2430          | 0.7778   |
| 0.0           | 39.0  | 8385  | 2.2389          | 0.7778   |
| 0.0           | 40.0  | 8600  | 2.2433          | 0.7778   |
| 0.0           | 41.0  | 8815  | 2.2306          | 0.7778   |
| 0.0           | 42.0  | 9030  | 2.2253          | 0.7778   |
| 0.0           | 43.0  | 9245  | 2.2215          | 0.7778   |
| 0.0           | 44.0  | 9460  | 2.2183          | 0.7778   |
| 0.0           | 45.0  | 9675  | 2.2187          | 0.7778   |
| 0.0           | 46.0  | 9890  | 2.2190          | 0.7778   |
| 0.0           | 47.0  | 10105 | 2.2156          | 0.7778   |
| 0.0           | 48.0  | 10320 | 2.2160          | 0.7778   |
| 0.0           | 49.0  | 10535 | 2.2147          | 0.7778   |
| 0.0           | 50.0  | 10750 | 2.2145          | 0.7778   |


### Framework versions

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