transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_sgd_lr00001_fold5
  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: 0.12195121951219512
---

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# hushem_1x_deit_tiny_sgd_lr00001_fold5

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6421
- Accuracy: 0.1220

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.6490          | 0.1220   |
| 1.6062        | 2.0   | 12   | 1.6487          | 0.1220   |
| 1.6062        | 3.0   | 18   | 1.6483          | 0.1220   |
| 1.6229        | 4.0   | 24   | 1.6480          | 0.1220   |
| 1.5995        | 5.0   | 30   | 1.6477          | 0.1220   |
| 1.5995        | 6.0   | 36   | 1.6474          | 0.1220   |
| 1.5906        | 7.0   | 42   | 1.6470          | 0.1220   |
| 1.5906        | 8.0   | 48   | 1.6468          | 0.1220   |
| 1.609         | 9.0   | 54   | 1.6465          | 0.1220   |
| 1.6018        | 10.0  | 60   | 1.6462          | 0.1220   |
| 1.6018        | 11.0  | 66   | 1.6459          | 0.1220   |
| 1.5944        | 12.0  | 72   | 1.6457          | 0.1220   |
| 1.5944        | 13.0  | 78   | 1.6454          | 0.1220   |
| 1.6013        | 14.0  | 84   | 1.6452          | 0.1220   |
| 1.5987        | 15.0  | 90   | 1.6449          | 0.1220   |
| 1.5987        | 16.0  | 96   | 1.6447          | 0.1220   |
| 1.5899        | 17.0  | 102  | 1.6445          | 0.1220   |
| 1.5899        | 18.0  | 108  | 1.6443          | 0.1220   |
| 1.626         | 19.0  | 114  | 1.6441          | 0.1220   |
| 1.5972        | 20.0  | 120  | 1.6439          | 0.1220   |
| 1.5972        | 21.0  | 126  | 1.6437          | 0.1220   |
| 1.5649        | 22.0  | 132  | 1.6436          | 0.1220   |
| 1.5649        | 23.0  | 138  | 1.6434          | 0.1220   |
| 1.6699        | 24.0  | 144  | 1.6433          | 0.1220   |
| 1.5696        | 25.0  | 150  | 1.6431          | 0.1220   |
| 1.5696        | 26.0  | 156  | 1.6430          | 0.1220   |
| 1.5743        | 27.0  | 162  | 1.6429          | 0.1220   |
| 1.5743        | 28.0  | 168  | 1.6427          | 0.1220   |
| 1.6236        | 29.0  | 174  | 1.6426          | 0.1220   |
| 1.5936        | 30.0  | 180  | 1.6426          | 0.1220   |
| 1.5936        | 31.0  | 186  | 1.6425          | 0.1220   |
| 1.5875        | 32.0  | 192  | 1.6424          | 0.1220   |
| 1.5875        | 33.0  | 198  | 1.6423          | 0.1220   |
| 1.6171        | 34.0  | 204  | 1.6423          | 0.1220   |
| 1.5897        | 35.0  | 210  | 1.6422          | 0.1220   |
| 1.5897        | 36.0  | 216  | 1.6422          | 0.1220   |
| 1.5725        | 37.0  | 222  | 1.6421          | 0.1220   |
| 1.5725        | 38.0  | 228  | 1.6421          | 0.1220   |
| 1.6227        | 39.0  | 234  | 1.6421          | 0.1220   |
| 1.5924        | 40.0  | 240  | 1.6421          | 0.1220   |
| 1.5924        | 41.0  | 246  | 1.6421          | 0.1220   |
| 1.5811        | 42.0  | 252  | 1.6421          | 0.1220   |
| 1.5811        | 43.0  | 258  | 1.6421          | 0.1220   |
| 1.6072        | 44.0  | 264  | 1.6421          | 0.1220   |
| 1.5938        | 45.0  | 270  | 1.6421          | 0.1220   |
| 1.5938        | 46.0  | 276  | 1.6421          | 0.1220   |
| 1.6243        | 47.0  | 282  | 1.6421          | 0.1220   |
| 1.6243        | 48.0  | 288  | 1.6421          | 0.1220   |
| 1.5633        | 49.0  | 294  | 1.6421          | 0.1220   |
| 1.6091        | 50.0  | 300  | 1.6421          | 0.1220   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
