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hushem_40x_deit_tiny_f1

Image Classification
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hushem_40x_deit_tiny_f1
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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_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: 0.8444444444444444
---

<!-- 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_f1

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: 0.6177
- Accuracy: 0.8444

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1057        | 1.0   | 107  | 0.4673          | 0.8222   |
| 0.0156        | 2.0   | 214  | 0.4217          | 0.8667   |
| 0.0006        | 2.99  | 321  | 0.3052          | 0.8889   |
| 0.0004        | 4.0   | 429  | 0.7953          | 0.8222   |
| 0.0004        | 5.0   | 536  | 0.2677          | 0.8667   |
| 0.0001        | 6.0   | 643  | 0.5139          | 0.8444   |
| 0.0           | 6.99  | 750  | 0.5825          | 0.8444   |
| 0.0           | 8.0   | 858  | 0.6043          | 0.8444   |
| 0.0           | 9.0   | 965  | 0.6155          | 0.8444   |
| 0.0           | 9.98  | 1070 | 0.6177          | 0.8444   |


### Framework versions

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