---
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: 0.9491525423728814
---

<!-- 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: 0.1253
- Accuracy: 0.9492

## 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        | 0.94  | 4    | 1.8882          | 0.1186   |
| No log        | 1.94  | 8    | 1.6799          | 0.3559   |
| No log        | 2.94  | 12   | 1.4260          | 0.5763   |
| No log        | 3.94  | 16   | 1.1092          | 0.6780   |
| 1.7242        | 4.94  | 20   | 0.8653          | 0.7458   |
| 1.7242        | 5.94  | 24   | 0.6787          | 0.7797   |
| 1.7242        | 6.94  | 28   | 0.5506          | 0.8305   |
| 1.7242        | 7.94  | 32   | 0.4174          | 0.8814   |
| 1.7242        | 8.94  | 36   | 0.3643          | 0.8814   |
| 0.8337        | 9.94  | 40   | 0.2680          | 0.9322   |
| 0.8337        | 10.94 | 44   | 0.2705          | 0.8983   |
| 0.8337        | 11.94 | 48   | 0.2270          | 0.9153   |
| 0.8337        | 12.94 | 52   | 0.1790          | 0.9492   |
| 0.8337        | 13.94 | 56   | 0.1694          | 0.9322   |
| 0.493         | 14.94 | 60   | 0.1776          | 0.9153   |
| 0.493         | 15.94 | 64   | 0.1831          | 0.9322   |
| 0.493         | 16.94 | 68   | 0.1765          | 0.9322   |
| 0.493         | 17.94 | 72   | 0.1575          | 0.9322   |
| 0.493         | 18.94 | 76   | 0.1472          | 0.9322   |
| 0.3966        | 19.94 | 80   | 0.1360          | 0.9322   |
| 0.3966        | 20.94 | 84   | 0.1448          | 0.9492   |
| 0.3966        | 21.94 | 88   | 0.1658          | 0.9322   |
| 0.3966        | 22.94 | 92   | 0.1652          | 0.9322   |
| 0.3966        | 23.94 | 96   | 0.1565          | 0.9322   |
| 0.3645        | 24.94 | 100  | 0.1701          | 0.9322   |
| 0.3645        | 25.94 | 104  | 0.1830          | 0.9322   |
| 0.3645        | 26.94 | 108  | 0.1682          | 0.9322   |
| 0.3645        | 27.94 | 112  | 0.1410          | 0.9492   |
| 0.3645        | 28.94 | 116  | 0.1291          | 0.9492   |
| 0.3358        | 29.94 | 120  | 0.1248          | 0.9492   |
| 0.3358        | 30.94 | 124  | 0.1275          | 0.9492   |
| 0.3358        | 31.94 | 128  | 0.1257          | 0.9492   |
| 0.3358        | 32.94 | 132  | 0.1288          | 0.9492   |
| 0.3358        | 33.94 | 136  | 0.1246          | 0.9492   |
| 0.3049        | 34.94 | 140  | 0.1219          | 0.9492   |
| 0.3049        | 35.94 | 144  | 0.1224          | 0.9492   |
| 0.3049        | 36.94 | 148  | 0.1246          | 0.9492   |
| 0.3049        | 37.94 | 152  | 0.1243          | 0.9492   |
| 0.3049        | 38.94 | 156  | 0.1248          | 0.9492   |
| 0.2962        | 39.94 | 160  | 0.1253          | 0.9492   |


### Framework versions

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