---
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: 0.9830508474576272
---

<!-- 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: 0.0375
- Accuracy: 0.9831

## 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: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.94  | 4    | 1.9124          | 0.1864   |
| No log        | 1.94  | 8    | 1.8095          | 0.2373   |
| No log        | 2.94  | 12   | 1.6757          | 0.3898   |
| No log        | 3.94  | 16   | 1.4906          | 0.5254   |
| 1.8286        | 4.94  | 20   | 1.2704          | 0.6441   |
| 1.8286        | 5.94  | 24   | 1.0685          | 0.6780   |
| 1.8286        | 6.94  | 28   | 0.8032          | 0.7458   |
| 1.8286        | 7.94  | 32   | 0.6309          | 0.7627   |
| 1.8286        | 8.94  | 36   | 0.4989          | 0.8475   |
| 0.9342        | 9.94  | 40   | 0.4063          | 0.8475   |
| 0.9342        | 10.94 | 44   | 0.2692          | 0.9153   |
| 0.9342        | 11.94 | 48   | 0.2736          | 0.8983   |
| 0.9342        | 12.94 | 52   | 0.2116          | 0.9322   |
| 0.9342        | 13.94 | 56   | 0.1498          | 0.9831   |
| 0.5151        | 14.94 | 60   | 0.1906          | 0.9153   |
| 0.5151        | 15.94 | 64   | 0.1698          | 0.9492   |
| 0.5151        | 16.94 | 68   | 0.1432          | 0.9492   |
| 0.5151        | 17.94 | 72   | 0.1682          | 0.9322   |
| 0.5151        | 18.94 | 76   | 0.1069          | 0.9831   |
| 0.4009        | 19.94 | 80   | 0.0821          | 0.9831   |
| 0.4009        | 20.94 | 84   | 0.0903          | 0.9831   |
| 0.4009        | 21.94 | 88   | 0.1281          | 0.9661   |
| 0.4009        | 22.94 | 92   | 0.0936          | 0.9831   |
| 0.4009        | 23.94 | 96   | 0.1059          | 0.9661   |
| 0.3482        | 24.94 | 100  | 0.1431          | 0.9492   |
| 0.3482        | 25.94 | 104  | 0.0899          | 0.9661   |
| 0.3482        | 26.94 | 108  | 0.0689          | 0.9661   |
| 0.3482        | 27.94 | 112  | 0.0751          | 0.9661   |
| 0.3482        | 28.94 | 116  | 0.0891          | 0.9661   |
| 0.3306        | 29.94 | 120  | 0.0523          | 0.9831   |
| 0.3306        | 30.94 | 124  | 0.0734          | 0.9831   |
| 0.3306        | 31.94 | 128  | 0.0746          | 0.9831   |
| 0.3306        | 32.94 | 132  | 0.0474          | 0.9661   |
| 0.3306        | 33.94 | 136  | 0.0443          | 0.9831   |
| 0.2871        | 34.94 | 140  | 0.0814          | 0.9831   |
| 0.2871        | 35.94 | 144  | 0.0691          | 0.9831   |
| 0.2871        | 36.94 | 148  | 0.0531          | 0.9831   |
| 0.2871        | 37.94 | 152  | 0.0614          | 0.9831   |
| 0.2871        | 38.94 | 156  | 0.0578          | 0.9831   |
| 0.2754        | 39.94 | 160  | 0.0520          | 0.9831   |
| 0.2754        | 40.94 | 164  | 0.0537          | 0.9831   |
| 0.2754        | 41.94 | 168  | 0.0447          | 0.9831   |
| 0.2754        | 42.94 | 172  | 0.0290          | 1.0      |
| 0.2754        | 43.94 | 176  | 0.0291          | 1.0      |
| 0.269         | 44.94 | 180  | 0.0326          | 0.9831   |
| 0.269         | 45.94 | 184  | 0.0330          | 0.9831   |
| 0.269         | 46.94 | 188  | 0.0348          | 0.9831   |
| 0.269         | 47.94 | 192  | 0.0347          | 0.9831   |
| 0.269         | 48.94 | 196  | 0.0347          | 0.9831   |
| 0.2615        | 49.94 | 200  | 0.0424          | 0.9831   |
| 0.2615        | 50.94 | 204  | 0.0451          | 0.9831   |
| 0.2615        | 51.94 | 208  | 0.0433          | 0.9831   |
| 0.2615        | 52.94 | 212  | 0.0352          | 0.9831   |
| 0.2615        | 53.94 | 216  | 0.0339          | 0.9831   |
| 0.2386        | 54.94 | 220  | 0.0339          | 0.9831   |
| 0.2386        | 55.94 | 224  | 0.0339          | 0.9831   |
| 0.2386        | 56.94 | 228  | 0.0348          | 0.9831   |
| 0.2386        | 57.94 | 232  | 0.0366          | 0.9831   |
| 0.2386        | 58.94 | 236  | 0.0374          | 0.9831   |
| 0.2362        | 59.94 | 240  | 0.0375          | 0.9831   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2