---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_base_adamax_001_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: 0.6341463414634146
---

<!-- 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_base_adamax_001_fold5

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co./facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8386
- Accuracy: 0.6341

## 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    | 1.4880          | 0.2683   |
| 1.545         | 2.0   | 12   | 1.4136          | 0.2439   |
| 1.545         | 3.0   | 18   | 1.3443          | 0.3171   |
| 1.396         | 4.0   | 24   | 1.1663          | 0.5122   |
| 1.3173        | 5.0   | 30   | 1.2019          | 0.4878   |
| 1.3173        | 6.0   | 36   | 1.2222          | 0.5122   |
| 1.3167        | 7.0   | 42   | 1.4763          | 0.2439   |
| 1.3167        | 8.0   | 48   | 1.1385          | 0.5610   |
| 1.2585        | 9.0   | 54   | 1.3584          | 0.3659   |
| 1.2419        | 10.0  | 60   | 1.0949          | 0.5122   |
| 1.2419        | 11.0  | 66   | 1.1100          | 0.4634   |
| 1.1714        | 12.0  | 72   | 1.2381          | 0.3902   |
| 1.1714        | 13.0  | 78   | 1.4043          | 0.4146   |
| 1.0593        | 14.0  | 84   | 1.1047          | 0.4878   |
| 1.0451        | 15.0  | 90   | 0.9907          | 0.4878   |
| 1.0451        | 16.0  | 96   | 1.3026          | 0.5122   |
| 0.8805        | 17.0  | 102  | 1.0082          | 0.6098   |
| 0.8805        | 18.0  | 108  | 1.1309          | 0.4634   |
| 0.8077        | 19.0  | 114  | 1.2367          | 0.5610   |
| 0.8096        | 20.0  | 120  | 1.4920          | 0.4878   |
| 0.8096        | 21.0  | 126  | 1.8018          | 0.4878   |
| 0.6582        | 22.0  | 132  | 1.5639          | 0.5854   |
| 0.6582        | 23.0  | 138  | 1.2712          | 0.4878   |
| 0.5106        | 24.0  | 144  | 1.1237          | 0.5854   |
| 0.4184        | 25.0  | 150  | 1.6831          | 0.5610   |
| 0.4184        | 26.0  | 156  | 2.0109          | 0.6098   |
| 0.2718        | 27.0  | 162  | 2.2516          | 0.6341   |
| 0.2718        | 28.0  | 168  | 2.0767          | 0.5610   |
| 0.1639        | 29.0  | 174  | 2.6167          | 0.5854   |
| 0.0535        | 30.0  | 180  | 2.8485          | 0.6341   |
| 0.0535        | 31.0  | 186  | 2.7124          | 0.6585   |
| 0.0454        | 32.0  | 192  | 2.8298          | 0.6585   |
| 0.0454        | 33.0  | 198  | 3.2241          | 0.6341   |
| 0.091         | 34.0  | 204  | 2.4575          | 0.5854   |
| 0.1109        | 35.0  | 210  | 3.7388          | 0.5610   |
| 0.1109        | 36.0  | 216  | 2.3707          | 0.7073   |
| 0.0834        | 37.0  | 222  | 2.5281          | 0.6341   |
| 0.0834        | 38.0  | 228  | 3.1120          | 0.6098   |
| 0.0051        | 39.0  | 234  | 2.7929          | 0.6341   |
| 0.0015        | 40.0  | 240  | 2.7025          | 0.6341   |
| 0.0015        | 41.0  | 246  | 2.8185          | 0.6341   |
| 0.0008        | 42.0  | 252  | 2.8386          | 0.6341   |
| 0.0008        | 43.0  | 258  | 2.8386          | 0.6341   |
| 0.0006        | 44.0  | 264  | 2.8386          | 0.6341   |
| 0.0007        | 45.0  | 270  | 2.8386          | 0.6341   |
| 0.0007        | 46.0  | 276  | 2.8386          | 0.6341   |
| 0.0007        | 47.0  | 282  | 2.8386          | 0.6341   |
| 0.0007        | 48.0  | 288  | 2.8386          | 0.6341   |
| 0.0006        | 49.0  | 294  | 2.8386          | 0.6341   |
| 0.0007        | 50.0  | 300  | 2.8386          | 0.6341   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1