---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_conflu_deneme_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: 0.7380952380952381
---

<!-- 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_conflu_deneme_fold4

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: 0.8165
- Accuracy: 0.7381

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.7088          | 0.2381   |
| 1.9076        | 2.0   | 12   | 1.4617          | 0.2381   |
| 1.9076        | 3.0   | 18   | 1.4512          | 0.2619   |
| 1.4689        | 4.0   | 24   | 1.3283          | 0.2381   |
| 1.3599        | 5.0   | 30   | 1.0112          | 0.6667   |
| 1.3599        | 6.0   | 36   | 1.1598          | 0.3810   |
| 1.2233        | 7.0   | 42   | 1.4323          | 0.4524   |
| 1.2233        | 8.0   | 48   | 0.9658          | 0.6667   |
| 1.0502        | 9.0   | 54   | 0.9166          | 0.6429   |
| 0.8636        | 10.0  | 60   | 0.8181          | 0.6190   |
| 0.8636        | 11.0  | 66   | 1.2729          | 0.5238   |
| 0.8856        | 12.0  | 72   | 0.7434          | 0.7381   |
| 0.8856        | 13.0  | 78   | 0.6840          | 0.7143   |
| 0.6672        | 14.0  | 84   | 0.9596          | 0.5238   |
| 0.5861        | 15.0  | 90   | 0.7243          | 0.7381   |
| 0.5861        | 16.0  | 96   | 0.8378          | 0.7143   |
| 0.4357        | 17.0  | 102  | 0.8165          | 0.7381   |
| 0.4357        | 18.0  | 108  | 0.8165          | 0.7381   |
| 0.4614        | 19.0  | 114  | 0.8165          | 0.7381   |
| 0.431         | 20.0  | 120  | 0.8165          | 0.7381   |


### Framework versions

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