---
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: 0.2180
- 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        | 0.57  | 1    | 1.7779          | 0.2727   |
| No log        | 1.57  | 2    | 1.7088          | 0.3182   |
| No log        | 2.57  | 3    | 1.5921          | 0.5455   |
| No log        | 3.57  | 4    | 1.4587          | 0.5909   |
| No log        | 4.57  | 5    | 1.3256          | 0.5455   |
| No log        | 5.57  | 6    | 1.2211          | 0.5      |
| No log        | 6.57  | 7    | 1.1066          | 0.6818   |
| No log        | 7.57  | 8    | 0.9768          | 0.7727   |
| No log        | 8.57  | 9    | 0.8590          | 0.8636   |
| No log        | 9.57  | 10   | 0.7718          | 0.9091   |
| No log        | 10.57 | 11   | 0.6999          | 0.9091   |
| No log        | 11.57 | 12   | 0.6385          | 0.9091   |
| No log        | 12.57 | 13   | 0.5761          | 0.9545   |
| No log        | 13.57 | 14   | 0.5189          | 0.9545   |
| No log        | 14.57 | 15   | 0.4646          | 0.9545   |
| No log        | 15.57 | 16   | 0.4137          | 0.9091   |
| No log        | 16.57 | 17   | 0.3679          | 0.9091   |
| No log        | 17.57 | 18   | 0.3291          | 0.9091   |
| No log        | 18.57 | 19   | 0.2937          | 0.9545   |
| 1.8863        | 19.57 | 20   | 0.2642          | 0.9545   |
| 1.8863        | 20.57 | 21   | 0.2366          | 0.9545   |
| 1.8863        | 21.57 | 22   | 0.2180          | 1.0      |
| 1.8863        | 22.57 | 23   | 0.2061          | 1.0      |
| 1.8863        | 23.57 | 24   | 0.1984          | 1.0      |
| 1.8863        | 24.57 | 25   | 0.1918          | 1.0      |
| 1.8863        | 25.57 | 26   | 0.1787          | 1.0      |
| 1.8863        | 26.57 | 27   | 0.1605          | 1.0      |
| 1.8863        | 27.57 | 28   | 0.1412          | 1.0      |
| 1.8863        | 28.57 | 29   | 0.1269          | 1.0      |
| 1.8863        | 29.57 | 30   | 0.1142          | 1.0      |
| 1.8863        | 30.57 | 31   | 0.1051          | 1.0      |
| 1.8863        | 31.57 | 32   | 0.0995          | 1.0      |
| 1.8863        | 32.57 | 33   | 0.0946          | 1.0      |
| 1.8863        | 33.57 | 34   | 0.0911          | 1.0      |
| 1.8863        | 34.57 | 35   | 0.0892          | 1.0      |
| 1.8863        | 35.57 | 36   | 0.0876          | 1.0      |
| 1.8863        | 36.57 | 37   | 0.0865          | 1.0      |
| 1.8863        | 37.57 | 38   | 0.0857          | 1.0      |
| 1.8863        | 38.57 | 39   | 0.0854          | 1.0      |
| 0.6775        | 39.57 | 40   | 0.0853          | 1.0      |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cpu
- Datasets 2.4.0
- Tokenizers 0.12.1