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_adamax_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: 0.7777777777777778
---

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# hushem_40x_deit_base_adamax_00001_fold1

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: 1.7464
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.175         | 1.0   | 215   | 0.7361          | 0.7556   |
| 0.0109        | 2.0   | 430   | 0.6497          | 0.8      |
| 0.0023        | 3.0   | 645   | 0.7453          | 0.8222   |
| 0.001         | 4.0   | 860   | 0.7854          | 0.8222   |
| 0.0006        | 5.0   | 1075  | 0.8105          | 0.8222   |
| 0.0004        | 6.0   | 1290  | 0.8328          | 0.8222   |
| 0.0003        | 7.0   | 1505  | 0.8638          | 0.8222   |
| 0.0002        | 8.0   | 1720  | 0.8701          | 0.8222   |
| 0.0002        | 9.0   | 1935  | 0.9048          | 0.8222   |
| 0.0001        | 10.0  | 2150  | 0.9203          | 0.8      |
| 0.0001        | 11.0  | 2365  | 0.9399          | 0.8      |
| 0.0001        | 12.0  | 2580  | 0.9611          | 0.8      |
| 0.0001        | 13.0  | 2795  | 0.9847          | 0.8      |
| 0.0001        | 14.0  | 3010  | 1.0078          | 0.8      |
| 0.0           | 15.0  | 3225  | 1.0165          | 0.8      |
| 0.0           | 16.0  | 3440  | 1.0509          | 0.8      |
| 0.0           | 17.0  | 3655  | 1.0662          | 0.8      |
| 0.0           | 18.0  | 3870  | 1.0960          | 0.8      |
| 0.0           | 19.0  | 4085  | 1.1102          | 0.8      |
| 0.0           | 20.0  | 4300  | 1.1333          | 0.8      |
| 0.0           | 21.0  | 4515  | 1.1560          | 0.8      |
| 0.0           | 22.0  | 4730  | 1.1835          | 0.8      |
| 0.0           | 23.0  | 4945  | 1.2066          | 0.8      |
| 0.0           | 24.0  | 5160  | 1.2238          | 0.8      |
| 0.0           | 25.0  | 5375  | 1.2452          | 0.8      |
| 0.0           | 26.0  | 5590  | 1.2607          | 0.8      |
| 0.0           | 27.0  | 5805  | 1.2985          | 0.8      |
| 0.0           | 28.0  | 6020  | 1.3142          | 0.7778   |
| 0.0           | 29.0  | 6235  | 1.3455          | 0.7778   |
| 0.0           | 30.0  | 6450  | 1.3849          | 0.7778   |
| 0.0           | 31.0  | 6665  | 1.4087          | 0.7778   |
| 0.0           | 32.0  | 6880  | 1.4316          | 0.7778   |
| 0.0           | 33.0  | 7095  | 1.4372          | 0.7778   |
| 0.0           | 34.0  | 7310  | 1.4578          | 0.7778   |
| 0.0           | 35.0  | 7525  | 1.5115          | 0.7778   |
| 0.0           | 36.0  | 7740  | 1.5151          | 0.7778   |
| 0.0           | 37.0  | 7955  | 1.5376          | 0.7778   |
| 0.0           | 38.0  | 8170  | 1.5694          | 0.7778   |
| 0.0           | 39.0  | 8385  | 1.5967          | 0.7778   |
| 0.0           | 40.0  | 8600  | 1.6099          | 0.7778   |
| 0.0           | 41.0  | 8815  | 1.6278          | 0.7778   |
| 0.0           | 42.0  | 9030  | 1.6372          | 0.7778   |
| 0.0           | 43.0  | 9245  | 1.6697          | 0.7778   |
| 0.0           | 44.0  | 9460  | 1.6889          | 0.7778   |
| 0.0           | 45.0  | 9675  | 1.6985          | 0.7778   |
| 0.0           | 46.0  | 9890  | 1.7202          | 0.7778   |
| 0.0           | 47.0  | 10105 | 1.7225          | 0.7778   |
| 0.0           | 48.0  | 10320 | 1.7406          | 0.7778   |
| 0.0           | 49.0  | 10535 | 1.7437          | 0.7778   |
| 0.0           | 50.0  | 10750 | 1.7464          | 0.7778   |


### Framework versions

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