---
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: 0.8571428571428571
---

<!-- 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: 0.7036
- Accuracy: 0.8571

## 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        | 1.0   | 1    | 1.9875          | 0.1429   |
| No log        | 2.0   | 2    | 1.9132          | 0.1429   |
| No log        | 3.0   | 3    | 1.7585          | 0.4286   |
| No log        | 4.0   | 4    | 1.5935          | 0.4286   |
| No log        | 5.0   | 5    | 1.5026          | 0.4286   |
| No log        | 6.0   | 6    | 1.4699          | 0.4286   |
| No log        | 7.0   | 7    | 1.4361          | 0.4286   |
| No log        | 8.0   | 8    | 1.3962          | 0.4286   |
| No log        | 9.0   | 9    | 1.3457          | 0.4286   |
| No log        | 10.0  | 10   | 1.2874          | 0.4286   |
| No log        | 11.0  | 11   | 1.2240          | 0.4286   |
| No log        | 12.0  | 12   | 1.1643          | 0.4286   |
| No log        | 13.0  | 13   | 1.1016          | 0.5714   |
| No log        | 14.0  | 14   | 1.0356          | 0.5714   |
| No log        | 15.0  | 15   | 0.9719          | 0.7143   |
| No log        | 16.0  | 16   | 0.9120          | 0.7143   |
| No log        | 17.0  | 17   | 0.8606          | 0.7143   |
| No log        | 18.0  | 18   | 0.8117          | 0.7143   |
| No log        | 19.0  | 19   | 0.7707          | 0.7143   |
| 0.5111        | 20.0  | 20   | 0.7367          | 0.7143   |
| 0.5111        | 21.0  | 21   | 0.7157          | 0.7143   |
| 0.5111        | 22.0  | 22   | 0.7067          | 0.7143   |
| 0.5111        | 23.0  | 23   | 0.7012          | 0.7143   |
| 0.5111        | 24.0  | 24   | 0.6977          | 0.7143   |
| 0.5111        | 25.0  | 25   | 0.6974          | 0.7143   |
| 0.5111        | 26.0  | 26   | 0.6977          | 0.7143   |
| 0.5111        | 27.0  | 27   | 0.7036          | 0.8571   |
| 0.5111        | 28.0  | 28   | 0.7074          | 0.8571   |
| 0.5111        | 29.0  | 29   | 0.7062          | 0.8571   |
| 0.5111        | 30.0  | 30   | 0.7056          | 0.8571   |
| 0.5111        | 31.0  | 31   | 0.7050          | 0.8571   |
| 0.5111        | 32.0  | 32   | 0.7050          | 0.8571   |
| 0.5111        | 33.0  | 33   | 0.7031          | 0.8571   |
| 0.5111        | 34.0  | 34   | 0.7016          | 0.8571   |
| 0.5111        | 35.0  | 35   | 0.6996          | 0.8571   |
| 0.5111        | 36.0  | 36   | 0.6971          | 0.8571   |
| 0.5111        | 37.0  | 37   | 0.6953          | 0.8571   |
| 0.5111        | 38.0  | 38   | 0.6939          | 0.8571   |
| 0.5111        | 39.0  | 39   | 0.6938          | 0.8571   |
| 0.1719        | 40.0  | 40   | 0.6936          | 0.8571   |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1