---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_base_sgd_001_fold4
  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: 0.5476190476190477
---

<!-- 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_5x_deit_base_sgd_001_fold4

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: 1.1129
- Accuracy: 0.5476

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4194        | 1.0   | 28   | 1.4029          | 0.1667   |
| 1.3727        | 2.0   | 56   | 1.3926          | 0.1667   |
| 1.3518        | 3.0   | 84   | 1.3828          | 0.1905   |
| 1.3497        | 4.0   | 112  | 1.3744          | 0.1905   |
| 1.3305        | 5.0   | 140  | 1.3656          | 0.2381   |
| 1.2982        | 6.0   | 168  | 1.3571          | 0.2619   |
| 1.2935        | 7.0   | 196  | 1.3493          | 0.2619   |
| 1.2822        | 8.0   | 224  | 1.3412          | 0.2857   |
| 1.2479        | 9.0   | 252  | 1.3334          | 0.3095   |
| 1.2377        | 10.0  | 280  | 1.3251          | 0.3333   |
| 1.2239        | 11.0  | 308  | 1.3164          | 0.3095   |
| 1.2188        | 12.0  | 336  | 1.3079          | 0.3095   |
| 1.2085        | 13.0  | 364  | 1.2995          | 0.3095   |
| 1.1996        | 14.0  | 392  | 1.2913          | 0.3333   |
| 1.1629        | 15.0  | 420  | 1.2831          | 0.3810   |
| 1.1847        | 16.0  | 448  | 1.2748          | 0.4048   |
| 1.1633        | 17.0  | 476  | 1.2664          | 0.4048   |
| 1.1189        | 18.0  | 504  | 1.2580          | 0.4048   |
| 1.1351        | 19.0  | 532  | 1.2497          | 0.4286   |
| 1.1255        | 20.0  | 560  | 1.2415          | 0.4286   |
| 1.0873        | 21.0  | 588  | 1.2339          | 0.4524   |
| 1.0919        | 22.0  | 616  | 1.2256          | 0.4524   |
| 1.0941        | 23.0  | 644  | 1.2182          | 0.4524   |
| 1.0702        | 24.0  | 672  | 1.2106          | 0.4762   |
| 1.0623        | 25.0  | 700  | 1.2031          | 0.4762   |
| 1.03          | 26.0  | 728  | 1.1958          | 0.4762   |
| 1.0368        | 27.0  | 756  | 1.1889          | 0.4762   |
| 1.0301        | 28.0  | 784  | 1.1818          | 0.4762   |
| 1.0348        | 29.0  | 812  | 1.1756          | 0.5      |
| 1.0312        | 30.0  | 840  | 1.1689          | 0.5      |
| 1.0387        | 31.0  | 868  | 1.1627          | 0.5238   |
| 1.0057        | 32.0  | 896  | 1.1569          | 0.5      |
| 1.0052        | 33.0  | 924  | 1.1517          | 0.5      |
| 0.9799        | 34.0  | 952  | 1.1467          | 0.5      |
| 1.0233        | 35.0  | 980  | 1.1420          | 0.5      |
| 0.9665        | 36.0  | 1008 | 1.1375          | 0.5      |
| 0.976         | 37.0  | 1036 | 1.1338          | 0.5      |
| 0.9856        | 38.0  | 1064 | 1.1303          | 0.5      |
| 0.9687        | 39.0  | 1092 | 1.1270          | 0.5      |
| 0.9553        | 40.0  | 1120 | 1.1240          | 0.5238   |
| 0.9573        | 41.0  | 1148 | 1.1217          | 0.5476   |
| 0.9651        | 42.0  | 1176 | 1.1193          | 0.5476   |
| 0.9476        | 43.0  | 1204 | 1.1173          | 0.5476   |
| 0.938         | 44.0  | 1232 | 1.1158          | 0.5476   |
| 0.9255        | 45.0  | 1260 | 1.1146          | 0.5476   |
| 0.9569        | 46.0  | 1288 | 1.1137          | 0.5476   |
| 0.9503        | 47.0  | 1316 | 1.1131          | 0.5476   |
| 0.9115        | 48.0  | 1344 | 1.1129          | 0.5476   |
| 0.9482        | 49.0  | 1372 | 1.1129          | 0.5476   |
| 0.9401        | 50.0  | 1400 | 1.1129          | 0.5476   |


### Framework versions

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