---
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_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: 0.24390243902439024
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_1x_deit_tiny_sgd_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: 1.7419
- Accuracy: 0.2439

## 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    | 1.7664          | 0.2439   |
| 1.7149        | 2.0   | 12   | 1.7652          | 0.2439   |
| 1.7149        | 3.0   | 18   | 1.7640          | 0.2439   |
| 1.7055        | 4.0   | 24   | 1.7627          | 0.2439   |
| 1.7032        | 5.0   | 30   | 1.7616          | 0.2439   |
| 1.7032        | 6.0   | 36   | 1.7604          | 0.2439   |
| 1.7195        | 7.0   | 42   | 1.7594          | 0.2439   |
| 1.7195        | 8.0   | 48   | 1.7584          | 0.2439   |
| 1.6458        | 9.0   | 54   | 1.7574          | 0.2439   |
| 1.7017        | 10.0  | 60   | 1.7564          | 0.2439   |
| 1.7017        | 11.0  | 66   | 1.7554          | 0.2439   |
| 1.7123        | 12.0  | 72   | 1.7545          | 0.2439   |
| 1.7123        | 13.0  | 78   | 1.7536          | 0.2439   |
| 1.6713        | 14.0  | 84   | 1.7528          | 0.2439   |
| 1.6849        | 15.0  | 90   | 1.7520          | 0.2439   |
| 1.6849        | 16.0  | 96   | 1.7512          | 0.2439   |
| 1.7051        | 17.0  | 102  | 1.7505          | 0.2439   |
| 1.7051        | 18.0  | 108  | 1.7498          | 0.2439   |
| 1.6541        | 19.0  | 114  | 1.7491          | 0.2439   |
| 1.7161        | 20.0  | 120  | 1.7484          | 0.2439   |
| 1.7161        | 21.0  | 126  | 1.7478          | 0.2439   |
| 1.6901        | 22.0  | 132  | 1.7472          | 0.2439   |
| 1.6901        | 23.0  | 138  | 1.7466          | 0.2439   |
| 1.6528        | 24.0  | 144  | 1.7461          | 0.2439   |
| 1.7234        | 25.0  | 150  | 1.7456          | 0.2439   |
| 1.7234        | 26.0  | 156  | 1.7451          | 0.2439   |
| 1.6839        | 27.0  | 162  | 1.7447          | 0.2439   |
| 1.6839        | 28.0  | 168  | 1.7443          | 0.2439   |
| 1.6859        | 29.0  | 174  | 1.7439          | 0.2439   |
| 1.6955        | 30.0  | 180  | 1.7436          | 0.2439   |
| 1.6955        | 31.0  | 186  | 1.7433          | 0.2439   |
| 1.7014        | 32.0  | 192  | 1.7430          | 0.2439   |
| 1.7014        | 33.0  | 198  | 1.7428          | 0.2439   |
| 1.6319        | 34.0  | 204  | 1.7426          | 0.2439   |
| 1.6586        | 35.0  | 210  | 1.7424          | 0.2439   |
| 1.6586        | 36.0  | 216  | 1.7422          | 0.2439   |
| 1.6897        | 37.0  | 222  | 1.7421          | 0.2439   |
| 1.6897        | 38.0  | 228  | 1.7420          | 0.2439   |
| 1.6863        | 39.0  | 234  | 1.7420          | 0.2439   |
| 1.6801        | 40.0  | 240  | 1.7419          | 0.2439   |
| 1.6801        | 41.0  | 246  | 1.7419          | 0.2439   |
| 1.7183        | 42.0  | 252  | 1.7419          | 0.2439   |
| 1.7183        | 43.0  | 258  | 1.7419          | 0.2439   |
| 1.6529        | 44.0  | 264  | 1.7419          | 0.2439   |
| 1.6913        | 45.0  | 270  | 1.7419          | 0.2439   |
| 1.6913        | 46.0  | 276  | 1.7419          | 0.2439   |
| 1.7139        | 47.0  | 282  | 1.7419          | 0.2439   |
| 1.7139        | 48.0  | 288  | 1.7419          | 0.2439   |
| 1.6464        | 49.0  | 294  | 1.7419          | 0.2439   |
| 1.6966        | 50.0  | 300  | 1.7419          | 0.2439   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0