---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_f1
  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: 0.8
---

<!-- 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_small_f1

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7923
- Accuracy: 0.8

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1638        | 0.99  | 53   | 0.4948          | 0.8222   |
| 0.018         | 1.99  | 107  | 0.8208          | 0.7556   |
| 0.0086        | 3.0   | 161  | 0.6473          | 0.8667   |
| 0.0011        | 4.0   | 215  | 0.7960          | 0.7556   |
| 0.0003        | 4.99  | 268  | 0.8013          | 0.7556   |
| 0.0001        | 5.99  | 322  | 0.8035          | 0.8      |
| 0.0001        | 7.0   | 376  | 0.7952          | 0.8      |
| 0.0001        | 8.0   | 430  | 0.7939          | 0.8      |
| 0.0001        | 8.99  | 483  | 0.7931          | 0.8      |
| 0.0001        | 9.86  | 530  | 0.7923          | 0.8      |


### Framework versions

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