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_sgd_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: 0.5813953488372093
---

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# hushem_40x_deit_small_sgd_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: 1.0466
- Accuracy: 0.5814

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.6887        | 1.0   | 217   | 1.4610          | 0.2558   |
| 1.5962        | 2.0   | 434   | 1.3845          | 0.3488   |
| 1.5124        | 3.0   | 651   | 1.3560          | 0.3721   |
| 1.442         | 4.0   | 868   | 1.3419          | 0.3721   |
| 1.41          | 5.0   | 1085  | 1.3313          | 0.3488   |
| 1.3709        | 6.0   | 1302  | 1.3218          | 0.3721   |
| 1.3157        | 7.0   | 1519  | 1.3125          | 0.3721   |
| 1.3328        | 8.0   | 1736  | 1.3039          | 0.3488   |
| 1.3107        | 9.0   | 1953  | 1.2950          | 0.3488   |
| 1.2568        | 10.0  | 2170  | 1.2861          | 0.3488   |
| 1.2226        | 11.0  | 2387  | 1.2769          | 0.3256   |
| 1.198         | 12.0  | 2604  | 1.2671          | 0.3256   |
| 1.232         | 13.0  | 2821  | 1.2570          | 0.3488   |
| 1.1803        | 14.0  | 3038  | 1.2472          | 0.3488   |
| 1.214         | 15.0  | 3255  | 1.2376          | 0.3488   |
| 1.208         | 16.0  | 3472  | 1.2274          | 0.3953   |
| 1.1406        | 17.0  | 3689  | 1.2176          | 0.3953   |
| 1.1243        | 18.0  | 3906  | 1.2072          | 0.3953   |
| 1.1316        | 19.0  | 4123  | 1.1970          | 0.4884   |
| 1.1119        | 20.0  | 4340  | 1.1873          | 0.4884   |
| 1.117         | 21.0  | 4557  | 1.1775          | 0.5116   |
| 1.0609        | 22.0  | 4774  | 1.1681          | 0.5116   |
| 1.0751        | 23.0  | 4991  | 1.1588          | 0.5581   |
| 1.058         | 24.0  | 5208  | 1.1499          | 0.5581   |
| 1.0301        | 25.0  | 5425  | 1.1417          | 0.5581   |
| 1.089         | 26.0  | 5642  | 1.1338          | 0.5581   |
| 0.9909        | 27.0  | 5859  | 1.1255          | 0.5814   |
| 0.9932        | 28.0  | 6076  | 1.1180          | 0.5814   |
| 1.026         | 29.0  | 6293  | 1.1110          | 0.5814   |
| 1.0236        | 30.0  | 6510  | 1.1044          | 0.5814   |
| 1.0169        | 31.0  | 6727  | 1.0980          | 0.5814   |
| 1.0049        | 32.0  | 6944  | 1.0921          | 0.5814   |
| 1.0261        | 33.0  | 7161  | 1.0868          | 0.5814   |
| 0.994         | 34.0  | 7378  | 1.0819          | 0.5814   |
| 0.9887        | 35.0  | 7595  | 1.0769          | 0.5581   |
| 1.0137        | 36.0  | 7812  | 1.0725          | 0.5581   |
| 0.9359        | 37.0  | 8029  | 1.0687          | 0.5581   |
| 0.9531        | 38.0  | 8246  | 1.0651          | 0.5581   |
| 0.9682        | 39.0  | 8463  | 1.0620          | 0.5581   |
| 0.9947        | 40.0  | 8680  | 1.0590          | 0.5581   |
| 0.9063        | 41.0  | 8897  | 1.0565          | 0.5581   |
| 1.0195        | 42.0  | 9114  | 1.0543          | 0.5581   |
| 0.966         | 43.0  | 9331  | 1.0523          | 0.5581   |
| 0.9409        | 44.0  | 9548  | 1.0506          | 0.5581   |
| 0.9327        | 45.0  | 9765  | 1.0492          | 0.5581   |
| 0.9575        | 46.0  | 9982  | 1.0481          | 0.5814   |
| 0.9627        | 47.0  | 10199 | 1.0474          | 0.5814   |
| 0.9553        | 48.0  | 10416 | 1.0469          | 0.5814   |
| 0.9631        | 49.0  | 10633 | 1.0467          | 0.5814   |
| 0.944         | 50.0  | 10850 | 1.0466          | 0.5814   |


### Framework versions

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