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_0001_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: 0.8604651162790697
---

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# hushem_40x_deit_small_rms_0001_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: 2.3623
- Accuracy: 0.8605

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.162         | 1.0   | 217   | 0.7397          | 0.8140   |
| 0.0554        | 2.0   | 434   | 0.5902          | 0.8605   |
| 0.0178        | 3.0   | 651   | 1.1734          | 0.8605   |
| 0.0009        | 4.0   | 868   | 1.2319          | 0.8372   |
| 0.0013        | 5.0   | 1085  | 1.7982          | 0.7442   |
| 0.0274        | 6.0   | 1302  | 1.0518          | 0.8140   |
| 0.0022        | 7.0   | 1519  | 1.2789          | 0.7907   |
| 0.0002        | 8.0   | 1736  | 1.6091          | 0.7907   |
| 0.0002        | 9.0   | 1953  | 1.3608          | 0.7907   |
| 0.0001        | 10.0  | 2170  | 1.7662          | 0.7674   |
| 0.0001        | 11.0  | 2387  | 1.4719          | 0.8372   |
| 0.0001        | 12.0  | 2604  | 0.9802          | 0.8837   |
| 0.0537        | 13.0  | 2821  | 1.7727          | 0.8140   |
| 0.0           | 14.0  | 3038  | 1.4355          | 0.8372   |
| 0.0002        | 15.0  | 3255  | 1.2526          | 0.8140   |
| 0.0071        | 16.0  | 3472  | 1.9556          | 0.7674   |
| 0.0           | 17.0  | 3689  | 1.8517          | 0.7907   |
| 0.0016        | 18.0  | 3906  | 1.4335          | 0.8372   |
| 0.0124        | 19.0  | 4123  | 1.3513          | 0.7907   |
| 0.0235        | 20.0  | 4340  | 2.0239          | 0.7907   |
| 0.0           | 21.0  | 4557  | 1.2893          | 0.8605   |
| 0.0           | 22.0  | 4774  | 1.3114          | 0.8605   |
| 0.0           | 23.0  | 4991  | 1.3523          | 0.8605   |
| 0.0           | 24.0  | 5208  | 1.4204          | 0.8372   |
| 0.0           | 25.0  | 5425  | 1.5136          | 0.8372   |
| 0.0           | 26.0  | 5642  | 1.6287          | 0.8605   |
| 0.0           | 27.0  | 5859  | 1.7481          | 0.8605   |
| 0.0           | 28.0  | 6076  | 1.8569          | 0.8605   |
| 0.0           | 29.0  | 6293  | 1.9482          | 0.8605   |
| 0.0           | 30.0  | 6510  | 2.0219          | 0.8605   |
| 0.0           | 31.0  | 6727  | 2.0881          | 0.8605   |
| 0.0           | 32.0  | 6944  | 2.1406          | 0.8605   |
| 0.0           | 33.0  | 7161  | 2.1867          | 0.8605   |
| 0.0           | 34.0  | 7378  | 2.2231          | 0.8605   |
| 0.0           | 35.0  | 7595  | 2.2508          | 0.8605   |
| 0.0           | 36.0  | 7812  | 2.2725          | 0.8605   |
| 0.0           | 37.0  | 8029  | 2.2899          | 0.8605   |
| 0.0           | 38.0  | 8246  | 2.3039          | 0.8605   |
| 0.0           | 39.0  | 8463  | 2.3156          | 0.8605   |
| 0.0           | 40.0  | 8680  | 2.3253          | 0.8605   |
| 0.0           | 41.0  | 8897  | 2.3335          | 0.8605   |
| 0.0           | 42.0  | 9114  | 2.3403          | 0.8605   |
| 0.0           | 43.0  | 9331  | 2.3460          | 0.8605   |
| 0.0           | 44.0  | 9548  | 2.3507          | 0.8605   |
| 0.0           | 45.0  | 9765  | 2.3545          | 0.8605   |
| 0.0           | 46.0  | 9982  | 2.3575          | 0.8605   |
| 0.0           | 47.0  | 10199 | 2.3597          | 0.8605   |
| 0.0           | 48.0  | 10416 | 2.3612          | 0.8605   |
| 0.0           | 49.0  | 10633 | 2.3621          | 0.8605   |
| 0.0           | 50.0  | 10850 | 2.3623          | 0.8605   |


### Framework versions

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