---
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_00001_fold2
  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: 0.5555555555555556
---

<!-- 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_00001_fold2

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: 1.2691
- Accuracy: 0.5556

## 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    | 1.3747          | 0.2222   |
| 1.3344        | 2.0   | 12   | 1.3328          | 0.3333   |
| 1.3344        | 3.0   | 18   | 1.2950          | 0.3778   |
| 1.1589        | 4.0   | 24   | 1.2639          | 0.4222   |
| 1.0046        | 5.0   | 30   | 1.2362          | 0.4667   |
| 1.0046        | 6.0   | 36   | 1.2118          | 0.5111   |
| 0.8105        | 7.0   | 42   | 1.1924          | 0.5111   |
| 0.8105        | 8.0   | 48   | 1.1812          | 0.5111   |
| 0.6759        | 9.0   | 54   | 1.1724          | 0.4889   |
| 0.5237        | 10.0  | 60   | 1.1564          | 0.5333   |
| 0.5237        | 11.0  | 66   | 1.1490          | 0.5333   |
| 0.4159        | 12.0  | 72   | 1.1389          | 0.5333   |
| 0.4159        | 13.0  | 78   | 1.1320          | 0.5556   |
| 0.3256        | 14.0  | 84   | 1.1287          | 0.5333   |
| 0.2501        | 15.0  | 90   | 1.1375          | 0.5333   |
| 0.2501        | 16.0  | 96   | 1.1291          | 0.5333   |
| 0.2011        | 17.0  | 102  | 1.1342          | 0.5333   |
| 0.2011        | 18.0  | 108  | 1.1537          | 0.5333   |
| 0.1629        | 19.0  | 114  | 1.1612          | 0.5333   |
| 0.1297        | 20.0  | 120  | 1.1554          | 0.5333   |
| 0.1297        | 21.0  | 126  | 1.1646          | 0.5333   |
| 0.105         | 22.0  | 132  | 1.1740          | 0.5333   |
| 0.105         | 23.0  | 138  | 1.1835          | 0.5333   |
| 0.0899        | 24.0  | 144  | 1.1913          | 0.5333   |
| 0.0683        | 25.0  | 150  | 1.2006          | 0.5333   |
| 0.0683        | 26.0  | 156  | 1.2072          | 0.5556   |
| 0.0612        | 27.0  | 162  | 1.2095          | 0.5556   |
| 0.0612        | 28.0  | 168  | 1.2218          | 0.5556   |
| 0.0476        | 29.0  | 174  | 1.2356          | 0.5556   |
| 0.0433        | 30.0  | 180  | 1.2335          | 0.5556   |
| 0.0433        | 31.0  | 186  | 1.2371          | 0.5556   |
| 0.0387        | 32.0  | 192  | 1.2442          | 0.5556   |
| 0.0387        | 33.0  | 198  | 1.2507          | 0.5556   |
| 0.0349        | 34.0  | 204  | 1.2533          | 0.5556   |
| 0.0342        | 35.0  | 210  | 1.2544          | 0.5556   |
| 0.0342        | 36.0  | 216  | 1.2556          | 0.5556   |
| 0.0314        | 37.0  | 222  | 1.2581          | 0.5556   |
| 0.0314        | 38.0  | 228  | 1.2633          | 0.5556   |
| 0.0273        | 39.0  | 234  | 1.2676          | 0.5556   |
| 0.0293        | 40.0  | 240  | 1.2685          | 0.5556   |
| 0.0293        | 41.0  | 246  | 1.2690          | 0.5556   |
| 0.0278        | 42.0  | 252  | 1.2691          | 0.5556   |
| 0.0278        | 43.0  | 258  | 1.2691          | 0.5556   |
| 0.0273        | 44.0  | 264  | 1.2691          | 0.5556   |
| 0.0276        | 45.0  | 270  | 1.2691          | 0.5556   |
| 0.0276        | 46.0  | 276  | 1.2691          | 0.5556   |
| 0.0276        | 47.0  | 282  | 1.2691          | 0.5556   |
| 0.0276        | 48.0  | 288  | 1.2691          | 0.5556   |
| 0.0275        | 49.0  | 294  | 1.2691          | 0.5556   |
| 0.0279        | 50.0  | 300  | 1.2691          | 0.5556   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0