---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_tiny_f3
  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: 0.9069767441860465
---

<!-- 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_40x_deit_tiny_f3

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: 0.7420
- Accuracy: 0.9070

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1605        | 1.0   | 108  | 0.5491          | 0.7674   |
| 0.067         | 2.0   | 217  | 0.3900          | 0.9070   |
| 0.0289        | 3.0   | 325  | 0.7123          | 0.8372   |
| 0.0006        | 4.0   | 434  | 0.6304          | 0.9302   |
| 0.0039        | 5.0   | 542  | 0.7304          | 0.8837   |
| 0.0003        | 6.0   | 651  | 0.9750          | 0.8372   |
| 0.0           | 7.0   | 759  | 0.7131          | 0.8837   |
| 0.0           | 8.0   | 868  | 0.7257          | 0.9070   |
| 0.0           | 9.0   | 976  | 0.7388          | 0.9070   |
| 0.0           | 9.95  | 1080 | 0.7420          | 0.9070   |


### Framework versions

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