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_fold3
  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: 0.9534883720930233
---

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# hushem_40x_deit_small_rms_00001_fold3

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: 0.4522
- Accuracy: 0.9535

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0295        | 1.0   | 217   | 0.4206          | 0.8837   |
| 0.002         | 2.0   | 434   | 0.1981          | 0.9070   |
| 0.0001        | 3.0   | 651   | 0.1728          | 0.8837   |
| 0.0           | 4.0   | 868   | 0.2047          | 0.9070   |
| 0.0           | 5.0   | 1085  | 0.2712          | 0.9070   |
| 0.0           | 6.0   | 1302  | 0.2693          | 0.9302   |
| 0.0           | 7.0   | 1519  | 0.3423          | 0.9070   |
| 0.0           | 8.0   | 1736  | 0.3994          | 0.9302   |
| 0.0           | 9.0   | 1953  | 0.3966          | 0.9302   |
| 0.0           | 10.0  | 2170  | 0.5128          | 0.9302   |
| 0.0           | 11.0  | 2387  | 0.4001          | 0.9302   |
| 0.0           | 12.0  | 2604  | 0.5315          | 0.9302   |
| 0.0           | 13.0  | 2821  | 0.5591          | 0.9302   |
| 0.0           | 14.0  | 3038  | 0.5631          | 0.9302   |
| 0.0           | 15.0  | 3255  | 0.4505          | 0.9302   |
| 0.0           | 16.0  | 3472  | 0.4593          | 0.9302   |
| 0.0           | 17.0  | 3689  | 0.5550          | 0.9302   |
| 0.0           | 18.0  | 3906  | 0.4957          | 0.9302   |
| 0.0           | 19.0  | 4123  | 0.4675          | 0.9302   |
| 0.0           | 20.0  | 4340  | 0.4440          | 0.9302   |
| 0.0           | 21.0  | 4557  | 0.5276          | 0.9302   |
| 0.0           | 22.0  | 4774  | 0.5480          | 0.9302   |
| 0.0           | 23.0  | 4991  | 0.4757          | 0.9302   |
| 0.0           | 24.0  | 5208  | 0.4990          | 0.9302   |
| 0.0           | 25.0  | 5425  | 0.4333          | 0.9535   |
| 0.0           | 26.0  | 5642  | 0.4085          | 0.9535   |
| 0.0           | 27.0  | 5859  | 0.4460          | 0.9535   |
| 0.0           | 28.0  | 6076  | 0.4859          | 0.9302   |
| 0.0           | 29.0  | 6293  | 0.4427          | 0.9302   |
| 0.0           | 30.0  | 6510  | 0.4450          | 0.9535   |
| 0.0           | 31.0  | 6727  | 0.4625          | 0.9535   |
| 0.0           | 32.0  | 6944  | 0.4421          | 0.9535   |
| 0.0           | 33.0  | 7161  | 0.4667          | 0.9302   |
| 0.0           | 34.0  | 7378  | 0.4474          | 0.9535   |
| 0.0           | 35.0  | 7595  | 0.4297          | 0.9535   |
| 0.0           | 36.0  | 7812  | 0.4695          | 0.9535   |
| 0.0           | 37.0  | 8029  | 0.4421          | 0.9535   |
| 0.0           | 38.0  | 8246  | 0.4281          | 0.9535   |
| 0.0           | 39.0  | 8463  | 0.4143          | 0.9535   |
| 0.0           | 40.0  | 8680  | 0.4529          | 0.9535   |
| 0.0           | 41.0  | 8897  | 0.4584          | 0.9535   |
| 0.0           | 42.0  | 9114  | 0.4637          | 0.9535   |
| 0.0           | 43.0  | 9331  | 0.4580          | 0.9535   |
| 0.0           | 44.0  | 9548  | 0.4337          | 0.9535   |
| 0.0           | 45.0  | 9765  | 0.4550          | 0.9535   |
| 0.0           | 46.0  | 9982  | 0.4612          | 0.9535   |
| 0.0           | 47.0  | 10199 | 0.4403          | 0.9535   |
| 0.0           | 48.0  | 10416 | 0.4548          | 0.9535   |
| 0.0           | 49.0  | 10633 | 0.4544          | 0.9535   |
| 0.0           | 50.0  | 10850 | 0.4522          | 0.9535   |


### Framework versions

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