---
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: 0.1787
- 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        | 0.8   | 1    | 2.0794          | 0.0588   |
| No log        | 1.8   | 2    | 2.0047          | 0.1176   |
| No log        | 2.8   | 3    | 1.8666          | 0.1765   |
| No log        | 3.8   | 4    | 1.6800          | 0.2353   |
| No log        | 4.8   | 5    | 1.4622          | 0.3529   |
| No log        | 5.8   | 6    | 1.2880          | 0.5882   |
| No log        | 6.8   | 7    | 1.1316          | 0.8824   |
| No log        | 7.8   | 8    | 0.9925          | 0.8824   |
| No log        | 8.8   | 9    | 0.8822          | 0.8824   |
| No log        | 9.8   | 10   | 0.7928          | 0.8824   |
| No log        | 10.8  | 11   | 0.7266          | 0.8824   |
| No log        | 11.8  | 12   | 0.6715          | 0.8824   |
| No log        | 12.8  | 13   | 0.6238          | 0.8824   |
| No log        | 13.8  | 14   | 0.5793          | 0.8824   |
| No log        | 14.8  | 15   | 0.5423          | 0.8824   |
| No log        | 15.8  | 16   | 0.5103          | 0.8824   |
| No log        | 16.8  | 17   | 0.4865          | 0.9412   |
| No log        | 17.8  | 18   | 0.4635          | 0.9412   |
| No log        | 18.8  | 19   | 0.4399          | 0.9412   |
| 1.3142        | 19.8  | 20   | 0.4119          | 0.9412   |
| 1.3142        | 20.8  | 21   | 0.3843          | 0.9412   |
| 1.3142        | 21.8  | 22   | 0.3497          | 0.9412   |
| 1.3142        | 22.8  | 23   | 0.3161          | 0.9412   |
| 1.3142        | 23.8  | 24   | 0.2850          | 0.9412   |
| 1.3142        | 24.8  | 25   | 0.2581          | 0.9412   |
| 1.3142        | 25.8  | 26   | 0.2363          | 0.9412   |
| 1.3142        | 26.8  | 27   | 0.2179          | 0.9412   |
| 1.3142        | 27.8  | 28   | 0.2029          | 0.9412   |
| 1.3142        | 28.8  | 29   | 0.1903          | 0.9412   |
| 1.3142        | 29.8  | 30   | 0.1787          | 1.0      |
| 1.3142        | 30.8  | 31   | 0.1676          | 1.0      |
| 1.3142        | 31.8  | 32   | 0.1581          | 1.0      |
| 1.3142        | 32.8  | 33   | 0.1487          | 1.0      |
| 1.3142        | 33.8  | 34   | 0.1410          | 1.0      |
| 1.3142        | 34.8  | 35   | 0.1349          | 1.0      |
| 1.3142        | 35.8  | 36   | 0.1301          | 1.0      |
| 1.3142        | 36.8  | 37   | 0.1266          | 1.0      |
| 1.3142        | 37.8  | 38   | 0.1243          | 1.0      |
| 1.3142        | 38.8  | 39   | 0.1230          | 1.0      |
| 0.4316        | 39.8  | 40   | 0.1223          | 1.0      |


### Framework versions

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