---
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_lr001_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: 0.5365853658536586
---

<!-- 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_lr001_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: 1.0599
- Accuracy: 0.5366

## 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: 0.001
- 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    | 2.6067          | 0.2439   |
| 4.0909        | 2.0   | 12   | 1.8085          | 0.2439   |
| 4.0909        | 3.0   | 18   | 1.7809          | 0.2439   |
| 2.0948        | 4.0   | 24   | 1.7586          | 0.2439   |
| 1.6719        | 5.0   | 30   | 1.5135          | 0.2439   |
| 1.6719        | 6.0   | 36   | 1.7849          | 0.2683   |
| 1.5694        | 7.0   | 42   | 1.4636          | 0.3902   |
| 1.5694        | 8.0   | 48   | 1.4809          | 0.2683   |
| 1.519         | 9.0   | 54   | 1.3587          | 0.3415   |
| 1.5241        | 10.0  | 60   | 1.3823          | 0.2439   |
| 1.5241        | 11.0  | 66   | 1.3645          | 0.3415   |
| 1.4557        | 12.0  | 72   | 1.2525          | 0.3659   |
| 1.4557        | 13.0  | 78   | 1.2955          | 0.3171   |
| 1.3674        | 14.0  | 84   | 1.3174          | 0.3415   |
| 1.3868        | 15.0  | 90   | 1.2787          | 0.3415   |
| 1.3868        | 16.0  | 96   | 1.6408          | 0.2683   |
| 1.3152        | 17.0  | 102  | 1.2750          | 0.3171   |
| 1.3152        | 18.0  | 108  | 1.0560          | 0.5366   |
| 1.2693        | 19.0  | 114  | 1.3256          | 0.4878   |
| 1.2554        | 20.0  | 120  | 1.3190          | 0.3902   |
| 1.2554        | 21.0  | 126  | 1.2498          | 0.3902   |
| 1.1813        | 22.0  | 132  | 1.2514          | 0.3902   |
| 1.1813        | 23.0  | 138  | 1.0907          | 0.5366   |
| 1.1113        | 24.0  | 144  | 1.2821          | 0.3415   |
| 1.1728        | 25.0  | 150  | 1.1433          | 0.4878   |
| 1.1728        | 26.0  | 156  | 1.0143          | 0.5366   |
| 1.1037        | 27.0  | 162  | 0.9542          | 0.5854   |
| 1.1037        | 28.0  | 168  | 1.1443          | 0.5122   |
| 1.0914        | 29.0  | 174  | 1.0904          | 0.4878   |
| 1.1385        | 30.0  | 180  | 1.1995          | 0.4146   |
| 1.1385        | 31.0  | 186  | 0.9746          | 0.6098   |
| 1.0636        | 32.0  | 192  | 1.1104          | 0.4634   |
| 1.0636        | 33.0  | 198  | 0.9890          | 0.6098   |
| 1.0129        | 34.0  | 204  | 1.2113          | 0.3902   |
| 0.999         | 35.0  | 210  | 1.0001          | 0.6098   |
| 0.999         | 36.0  | 216  | 1.0972          | 0.5122   |
| 0.9802        | 37.0  | 222  | 1.1639          | 0.4390   |
| 0.9802        | 38.0  | 228  | 1.0730          | 0.5122   |
| 0.9625        | 39.0  | 234  | 1.0471          | 0.4878   |
| 0.9424        | 40.0  | 240  | 1.0692          | 0.5366   |
| 0.9424        | 41.0  | 246  | 1.0654          | 0.5366   |
| 0.9521        | 42.0  | 252  | 1.0599          | 0.5366   |
| 0.9521        | 43.0  | 258  | 1.0599          | 0.5366   |
| 0.9184        | 44.0  | 264  | 1.0599          | 0.5366   |
| 0.9335        | 45.0  | 270  | 1.0599          | 0.5366   |
| 0.9335        | 46.0  | 276  | 1.0599          | 0.5366   |
| 0.9251        | 47.0  | 282  | 1.0599          | 0.5366   |
| 0.9251        | 48.0  | 288  | 1.0599          | 0.5366   |
| 0.9168        | 49.0  | 294  | 1.0599          | 0.5366   |
| 0.8964        | 50.0  | 300  | 1.0599          | 0.5366   |


### Framework versions

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