---
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: 0.9692307692307692
---

<!-- 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: 0.2293
- Accuracy: 0.9692

## 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        | 0.84  | 4    | 1.9335          | 0.1846   |
| No log        | 1.84  | 8    | 1.8364          | 0.2615   |
| No log        | 2.84  | 12   | 1.7054          | 0.3846   |
| No log        | 3.84  | 16   | 1.5629          | 0.4154   |
| 2.0106        | 4.84  | 20   | 1.3907          | 0.4769   |
| 2.0106        | 5.84  | 24   | 1.1984          | 0.5692   |
| 2.0106        | 6.84  | 28   | 0.9519          | 0.6615   |
| 2.0106        | 7.84  | 32   | 0.7510          | 0.7846   |
| 2.0106        | 8.84  | 36   | 0.5749          | 0.8615   |
| 1.1009        | 9.84  | 40   | 0.4244          | 0.9385   |
| 1.1009        | 10.84 | 44   | 0.3652          | 0.8923   |
| 1.1009        | 11.84 | 48   | 0.2735          | 0.9538   |
| 1.1009        | 12.84 | 52   | 0.2909          | 0.8923   |
| 1.1009        | 13.84 | 56   | 0.2293          | 0.9692   |
| 0.6329        | 14.84 | 60   | 0.2563          | 0.9077   |
| 0.6329        | 15.84 | 64   | 0.2218          | 0.9231   |
| 0.6329        | 16.84 | 68   | 0.2102          | 0.9538   |
| 0.6329        | 17.84 | 72   | 0.1829          | 0.9231   |
| 0.6329        | 18.84 | 76   | 0.1992          | 0.9231   |
| 0.497         | 19.84 | 80   | 0.1814          | 0.9231   |
| 0.497         | 20.84 | 84   | 0.1807          | 0.9385   |
| 0.497         | 21.84 | 88   | 0.1765          | 0.9538   |
| 0.497         | 22.84 | 92   | 0.1868          | 0.9231   |
| 0.497         | 23.84 | 96   | 0.2089          | 0.9385   |
| 0.4198        | 24.84 | 100  | 0.1898          | 0.9385   |
| 0.4198        | 25.84 | 104  | 0.2065          | 0.9231   |
| 0.4198        | 26.84 | 108  | 0.1845          | 0.9231   |
| 0.4198        | 27.84 | 112  | 0.1724          | 0.9231   |
| 0.4198        | 28.84 | 116  | 0.1612          | 0.9385   |
| 0.368         | 29.84 | 120  | 0.1538          | 0.9538   |
| 0.368         | 30.84 | 124  | 0.1568          | 0.9538   |
| 0.368         | 31.84 | 128  | 0.1475          | 0.9692   |
| 0.368         | 32.84 | 132  | 0.1453          | 0.9538   |
| 0.368         | 33.84 | 136  | 0.1576          | 0.9692   |
| 0.3709        | 34.84 | 140  | 0.1430          | 0.9692   |
| 0.3709        | 35.84 | 144  | 0.1384          | 0.9692   |
| 0.3709        | 36.84 | 148  | 0.1432          | 0.9692   |
| 0.3709        | 37.84 | 152  | 0.1347          | 0.9692   |
| 0.3709        | 38.84 | 156  | 0.1359          | 0.9538   |
| 0.3373        | 39.84 | 160  | 0.1597          | 0.9538   |
| 0.3373        | 40.84 | 164  | 0.1522          | 0.9692   |
| 0.3373        | 41.84 | 168  | 0.1477          | 0.9538   |
| 0.3373        | 42.84 | 172  | 0.1480          | 0.9692   |
| 0.3373        | 43.84 | 176  | 0.1472          | 0.9692   |
| 0.3342        | 44.84 | 180  | 0.1473          | 0.9692   |
| 0.3342        | 45.84 | 184  | 0.1458          | 0.9692   |
| 0.3342        | 46.84 | 188  | 0.1529          | 0.9692   |
| 0.3342        | 47.84 | 192  | 0.1550          | 0.9692   |
| 0.3342        | 48.84 | 196  | 0.1494          | 0.9692   |
| 0.2914        | 49.84 | 200  | 0.1470          | 0.9692   |
| 0.2914        | 50.84 | 204  | 0.1460          | 0.9692   |
| 0.2914        | 51.84 | 208  | 0.1478          | 0.9692   |
| 0.2914        | 52.84 | 212  | 0.1481          | 0.9692   |
| 0.2914        | 53.84 | 216  | 0.1461          | 0.9692   |
| 0.2736        | 54.84 | 220  | 0.1458          | 0.9692   |
| 0.2736        | 55.84 | 224  | 0.1438          | 0.9692   |
| 0.2736        | 56.84 | 228  | 0.1427          | 0.9692   |
| 0.2736        | 57.84 | 232  | 0.1418          | 0.9692   |
| 0.2736        | 58.84 | 236  | 0.1401          | 0.9692   |
| 0.2589        | 59.84 | 240  | 0.1399          | 0.9692   |


### Framework versions

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