---
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: 0.0447
- 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        | 0.86  | 3    | 1.7166          | 0.2245   |
| No log        | 1.86  | 6    | 1.5816          | 0.4082   |
| No log        | 2.86  | 9    | 1.4084          | 0.5510   |
| No log        | 3.86  | 12   | 1.1761          | 0.6327   |
| No log        | 4.86  | 15   | 0.9245          | 0.7347   |
| No log        | 5.86  | 18   | 0.6986          | 0.7959   |
| 1.608         | 6.86  | 21   | 0.5158          | 0.8367   |
| 1.608         | 7.86  | 24   | 0.3753          | 0.8776   |
| 1.608         | 8.86  | 27   | 0.3092          | 0.8980   |
| 1.608         | 9.86  | 30   | 0.2584          | 0.9388   |
| 1.608         | 10.86 | 33   | 0.2159          | 0.9184   |
| 1.608         | 11.86 | 36   | 0.1908          | 0.9592   |
| 1.608         | 12.86 | 39   | 0.1802          | 0.9592   |
| 0.6473        | 13.86 | 42   | 0.1682          | 0.9592   |
| 0.6473        | 14.86 | 45   | 0.1560          | 0.9592   |
| 0.6473        | 15.86 | 48   | 0.1322          | 0.9592   |
| 0.6473        | 16.86 | 51   | 0.1101          | 0.9592   |
| 0.6473        | 17.86 | 54   | 0.0938          | 0.9592   |
| 0.6473        | 18.86 | 57   | 0.0889          | 0.9796   |
| 0.3855        | 19.86 | 60   | 0.1025          | 0.9796   |
| 0.3855        | 20.86 | 63   | 0.0984          | 0.9796   |
| 0.3855        | 21.86 | 66   | 0.0867          | 0.9592   |
| 0.3855        | 22.86 | 69   | 0.0813          | 0.9592   |
| 0.3855        | 23.86 | 72   | 0.0768          | 0.9592   |
| 0.3855        | 24.86 | 75   | 0.0734          | 0.9796   |
| 0.3855        | 25.86 | 78   | 0.0698          | 0.9796   |
| 0.306         | 26.86 | 81   | 0.0618          | 0.9592   |
| 0.306         | 27.86 | 84   | 0.0547          | 0.9796   |
| 0.306         | 28.86 | 87   | 0.0538          | 0.9592   |
| 0.306         | 29.86 | 90   | 0.0487          | 0.9796   |
| 0.306         | 30.86 | 93   | 0.0447          | 1.0      |
| 0.306         | 31.86 | 96   | 0.0425          | 1.0      |
| 0.306         | 32.86 | 99   | 0.0451          | 1.0      |
| 0.2966        | 33.86 | 102  | 0.0497          | 1.0      |
| 0.2966        | 34.86 | 105  | 0.0558          | 1.0      |
| 0.2966        | 35.86 | 108  | 0.0582          | 0.9796   |
| 0.2966        | 36.86 | 111  | 0.0616          | 0.9592   |
| 0.2966        | 37.86 | 114  | 0.0657          | 0.9592   |
| 0.2966        | 38.86 | 117  | 0.0679          | 0.9592   |
| 0.2535        | 39.86 | 120  | 0.0684          | 0.9592   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1