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hushem_40x_deit_tiny_f4

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hushem_40x_deit_tiny_f4
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---
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_f4
  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: 0.9523809523809523
---

<!-- 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_f4

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: 0.1343
- Accuracy: 0.9524

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1784        | 1.0   | 109  | 0.2924          | 0.9048   |
| 0.0478        | 2.0   | 218  | 0.2362          | 0.8810   |
| 0.0048        | 2.99  | 327  | 0.2393          | 0.9286   |
| 0.0107        | 4.0   | 437  | 0.2679          | 0.8810   |
| 0.0008        | 5.0   | 546  | 0.1124          | 0.9524   |
| 0.0001        | 6.0   | 655  | 0.4513          | 0.9048   |
| 0.0           | 6.99  | 764  | 0.0770          | 0.9524   |
| 0.0           | 8.0   | 874  | 0.1185          | 0.9524   |
| 0.0           | 9.0   | 983  | 0.1295          | 0.9524   |
| 0.0           | 9.98  | 1090 | 0.1343          | 0.9524   |


### Framework versions

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