---
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_rms_lr00001_fold1
  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: 0.6888888888888889
---

<!-- 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_rms_lr00001_fold1

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: 1.2449
- Accuracy: 0.6889

## 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    | 1.2771          | 0.4      |
| 1.263         | 2.0   | 12   | 1.0784          | 0.5556   |
| 1.263         | 3.0   | 18   | 0.9616          | 0.5556   |
| 0.5461        | 4.0   | 24   | 1.0339          | 0.6889   |
| 0.2446        | 5.0   | 30   | 0.9939          | 0.6667   |
| 0.2446        | 6.0   | 36   | 1.2442          | 0.4889   |
| 0.0817        | 7.0   | 42   | 0.7980          | 0.6222   |
| 0.0817        | 8.0   | 48   | 0.8675          | 0.6444   |
| 0.0302        | 9.0   | 54   | 0.8969          | 0.6889   |
| 0.009         | 10.0  | 60   | 0.9399          | 0.6222   |
| 0.009         | 11.0  | 66   | 1.0591          | 0.7111   |
| 0.0037        | 12.0  | 72   | 1.0283          | 0.6667   |
| 0.0037        | 13.0  | 78   | 1.0855          | 0.6667   |
| 0.0025        | 14.0  | 84   | 1.1121          | 0.6667   |
| 0.0019        | 15.0  | 90   | 1.1082          | 0.6667   |
| 0.0019        | 16.0  | 96   | 1.1158          | 0.6667   |
| 0.0015        | 17.0  | 102  | 1.1382          | 0.6667   |
| 0.0015        | 18.0  | 108  | 1.1574          | 0.6667   |
| 0.0013        | 19.0  | 114  | 1.1739          | 0.6667   |
| 0.0011        | 20.0  | 120  | 1.1736          | 0.6667   |
| 0.0011        | 21.0  | 126  | 1.1594          | 0.6889   |
| 0.001         | 22.0  | 132  | 1.1738          | 0.6889   |
| 0.001         | 23.0  | 138  | 1.1962          | 0.6667   |
| 0.0009        | 24.0  | 144  | 1.1951          | 0.6889   |
| 0.0008        | 25.0  | 150  | 1.2004          | 0.6889   |
| 0.0008        | 26.0  | 156  | 1.1996          | 0.6889   |
| 0.0008        | 27.0  | 162  | 1.2076          | 0.6889   |
| 0.0008        | 28.0  | 168  | 1.2144          | 0.6889   |
| 0.0007        | 29.0  | 174  | 1.2117          | 0.6889   |
| 0.0007        | 30.0  | 180  | 1.2204          | 0.6889   |
| 0.0007        | 31.0  | 186  | 1.2217          | 0.6889   |
| 0.0006        | 32.0  | 192  | 1.2270          | 0.6889   |
| 0.0006        | 33.0  | 198  | 1.2321          | 0.6889   |
| 0.0006        | 34.0  | 204  | 1.2307          | 0.6889   |
| 0.0006        | 35.0  | 210  | 1.2313          | 0.6889   |
| 0.0006        | 36.0  | 216  | 1.2374          | 0.6889   |
| 0.0006        | 37.0  | 222  | 1.2446          | 0.6889   |
| 0.0006        | 38.0  | 228  | 1.2471          | 0.6889   |
| 0.0005        | 39.0  | 234  | 1.2452          | 0.6889   |
| 0.0006        | 40.0  | 240  | 1.2458          | 0.6889   |
| 0.0006        | 41.0  | 246  | 1.2454          | 0.6889   |
| 0.0005        | 42.0  | 252  | 1.2449          | 0.6889   |
| 0.0005        | 43.0  | 258  | 1.2449          | 0.6889   |
| 0.0005        | 44.0  | 264  | 1.2449          | 0.6889   |
| 0.0005        | 45.0  | 270  | 1.2449          | 0.6889   |
| 0.0005        | 46.0  | 276  | 1.2449          | 0.6889   |
| 0.0005        | 47.0  | 282  | 1.2449          | 0.6889   |
| 0.0005        | 48.0  | 288  | 1.2449          | 0.6889   |
| 0.0005        | 49.0  | 294  | 1.2449          | 0.6889   |
| 0.0005        | 50.0  | 300  | 1.2449          | 0.6889   |


### Framework versions

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