---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: delivery_truck_classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 1.0
---

<!-- 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. -->

# delivery_truck_classification

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0274
- Accuracy: 1.0

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.8   | 3    | 1.8912          | 0.0392   |
| No log        | 1.8   | 6    | 1.7519          | 0.2745   |
| No log        | 2.8   | 9    | 1.5549          | 0.4706   |
| No log        | 3.8   | 12   | 1.2851          | 0.6667   |
| No log        | 4.8   | 15   | 0.9968          | 0.7647   |
| No log        | 5.8   | 18   | 0.7826          | 0.7843   |
| 1.787         | 6.8   | 21   | 0.6010          | 0.8824   |
| 1.787         | 7.8   | 24   | 0.4301          | 0.9020   |
| 1.787         | 8.8   | 27   | 0.3233          | 0.8824   |
| 1.787         | 9.8   | 30   | 0.2303          | 0.9412   |
| 1.787         | 10.8  | 33   | 0.1871          | 1.0      |
| 1.787         | 11.8  | 36   | 0.1600          | 0.9608   |
| 1.787         | 12.8  | 39   | 0.1334          | 0.9804   |
| 0.7554        | 13.8  | 42   | 0.1025          | 1.0      |
| 0.7554        | 14.8  | 45   | 0.0909          | 1.0      |
| 0.7554        | 15.8  | 48   | 0.0733          | 1.0      |
| 0.7554        | 16.8  | 51   | 0.0625          | 1.0      |
| 0.7554        | 17.8  | 54   | 0.0602          | 1.0      |
| 0.7554        | 18.8  | 57   | 0.0613          | 1.0      |
| 0.4731        | 19.8  | 60   | 0.0506          | 1.0      |
| 0.4731        | 20.8  | 63   | 0.0588          | 1.0      |
| 0.4731        | 21.8  | 66   | 0.0655          | 0.9804   |
| 0.4731        | 22.8  | 69   | 0.0517          | 1.0      |
| 0.4731        | 23.8  | 72   | 0.0414          | 1.0      |
| 0.4731        | 24.8  | 75   | 0.0408          | 1.0      |
| 0.4731        | 25.8  | 78   | 0.0417          | 1.0      |
| 0.4248        | 26.8  | 81   | 0.0389          | 1.0      |
| 0.4248        | 27.8  | 84   | 0.0376          | 1.0      |
| 0.4248        | 28.8  | 87   | 0.0361          | 1.0      |
| 0.4248        | 29.8  | 90   | 0.0351          | 1.0      |
| 0.4248        | 30.8  | 93   | 0.0299          | 1.0      |
| 0.4248        | 31.8  | 96   | 0.0284          | 1.0      |
| 0.4248        | 32.8  | 99   | 0.0279          | 1.0      |
| 0.3657        | 33.8  | 102  | 0.0275          | 1.0      |
| 0.3657        | 34.8  | 105  | 0.0279          | 1.0      |
| 0.3657        | 35.8  | 108  | 0.0279          | 1.0      |
| 0.3657        | 36.8  | 111  | 0.0278          | 1.0      |
| 0.3657        | 37.8  | 114  | 0.0276          | 1.0      |
| 0.3657        | 38.8  | 117  | 0.0274          | 1.0      |
| 0.3115        | 39.8  | 120  | 0.0274          | 1.0      |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2