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_adamax_00001_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: 0.5121951219512195
---

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# hushem_1x_deit_tiny_adamax_00001_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: 0.9982
- Accuracy: 0.5122

## 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    | 1.3816          | 0.2927   |
| 1.4331        | 2.0   | 12   | 1.3595          | 0.2195   |
| 1.4331        | 3.0   | 18   | 1.3006          | 0.2927   |
| 1.2071        | 4.0   | 24   | 1.2477          | 0.3415   |
| 1.0931        | 5.0   | 30   | 1.2218          | 0.3659   |
| 1.0931        | 6.0   | 36   | 1.1904          | 0.3415   |
| 0.9583        | 7.0   | 42   | 1.2070          | 0.3659   |
| 0.9583        | 8.0   | 48   | 1.1804          | 0.3415   |
| 0.875         | 9.0   | 54   | 1.1663          | 0.3415   |
| 0.7821        | 10.0  | 60   | 1.1729          | 0.3659   |
| 0.7821        | 11.0  | 66   | 1.1600          | 0.3659   |
| 0.7082        | 12.0  | 72   | 1.1535          | 0.3659   |
| 0.7082        | 13.0  | 78   | 1.1283          | 0.3902   |
| 0.5865        | 14.0  | 84   | 1.1050          | 0.4146   |
| 0.5549        | 15.0  | 90   | 1.0989          | 0.4146   |
| 0.5549        | 16.0  | 96   | 1.0902          | 0.4146   |
| 0.4748        | 17.0  | 102  | 1.0889          | 0.4146   |
| 0.4748        | 18.0  | 108  | 1.0670          | 0.4146   |
| 0.4005        | 19.0  | 114  | 1.0529          | 0.4146   |
| 0.3717        | 20.0  | 120  | 1.0514          | 0.4146   |
| 0.3717        | 21.0  | 126  | 1.0589          | 0.4146   |
| 0.3189        | 22.0  | 132  | 1.0546          | 0.4146   |
| 0.3189        | 23.0  | 138  | 1.0253          | 0.4390   |
| 0.2768        | 24.0  | 144  | 1.0205          | 0.4390   |
| 0.2632        | 25.0  | 150  | 1.0386          | 0.4146   |
| 0.2632        | 26.0  | 156  | 1.0297          | 0.4390   |
| 0.2284        | 27.0  | 162  | 1.0322          | 0.4634   |
| 0.2284        | 28.0  | 168  | 1.0102          | 0.4634   |
| 0.196         | 29.0  | 174  | 1.0015          | 0.4878   |
| 0.1861        | 30.0  | 180  | 1.0070          | 0.4634   |
| 0.1861        | 31.0  | 186  | 1.0149          | 0.4878   |
| 0.1711        | 32.0  | 192  | 1.0173          | 0.4878   |
| 0.1711        | 33.0  | 198  | 1.0083          | 0.4878   |
| 0.1508        | 34.0  | 204  | 1.0068          | 0.5122   |
| 0.1433        | 35.0  | 210  | 0.9998          | 0.5122   |
| 0.1433        | 36.0  | 216  | 0.9984          | 0.5122   |
| 0.1371        | 37.0  | 222  | 0.9985          | 0.5122   |
| 0.1371        | 38.0  | 228  | 0.9983          | 0.5122   |
| 0.1311        | 39.0  | 234  | 0.9983          | 0.5122   |
| 0.1245        | 40.0  | 240  | 0.9977          | 0.5122   |
| 0.1245        | 41.0  | 246  | 0.9980          | 0.5122   |
| 0.1273        | 42.0  | 252  | 0.9982          | 0.5122   |
| 0.1273        | 43.0  | 258  | 0.9982          | 0.5122   |
| 0.1185        | 44.0  | 264  | 0.9982          | 0.5122   |
| 0.1259        | 45.0  | 270  | 0.9982          | 0.5122   |
| 0.1259        | 46.0  | 276  | 0.9982          | 0.5122   |
| 0.1239        | 47.0  | 282  | 0.9982          | 0.5122   |
| 0.1239        | 48.0  | 288  | 0.9982          | 0.5122   |
| 0.1264        | 49.0  | 294  | 0.9982          | 0.5122   |
| 0.1234        | 50.0  | 300  | 0.9982          | 0.5122   |


### Framework versions

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