---
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: 0.9846153846153847
---

<!-- 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: 0.0874
- Accuracy: 0.9846

## 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    | 1.8199          | 0.3231   |
| No log        | 1.84  | 8    | 1.7275          | 0.4154   |
| No log        | 2.84  | 12   | 1.6281          | 0.4615   |
| No log        | 3.84  | 16   | 1.5272          | 0.4615   |
| 1.9537        | 4.84  | 20   | 1.3668          | 0.5077   |
| 1.9537        | 5.84  | 24   | 1.0964          | 0.6      |
| 1.9537        | 6.84  | 28   | 0.7691          | 0.7846   |
| 1.9537        | 7.84  | 32   | 0.6370          | 0.8308   |
| 1.9537        | 8.84  | 36   | 0.4329          | 0.9077   |
| 1.0682        | 9.84  | 40   | 0.3518          | 0.9077   |
| 1.0682        | 10.84 | 44   | 0.3229          | 0.8923   |
| 1.0682        | 11.84 | 48   | 0.2324          | 0.9385   |
| 1.0682        | 12.84 | 52   | 0.2369          | 0.9385   |
| 1.0682        | 13.84 | 56   | 0.2119          | 0.9385   |
| 0.6335        | 14.84 | 60   | 0.1805          | 0.9385   |
| 0.6335        | 15.84 | 64   | 0.2135          | 0.9077   |
| 0.6335        | 16.84 | 68   | 0.1889          | 0.9231   |
| 0.6335        | 17.84 | 72   | 0.1601          | 0.9538   |
| 0.6335        | 18.84 | 76   | 0.1412          | 0.9692   |
| 0.5133        | 19.84 | 80   | 0.1497          | 0.9538   |
| 0.5133        | 20.84 | 84   | 0.1545          | 0.9538   |
| 0.5133        | 21.84 | 88   | 0.1298          | 0.9538   |
| 0.5133        | 22.84 | 92   | 0.1415          | 0.9538   |
| 0.5133        | 23.84 | 96   | 0.1685          | 0.9231   |
| 0.4383        | 24.84 | 100  | 0.1381          | 0.9385   |
| 0.4383        | 25.84 | 104  | 0.1296          | 0.9846   |
| 0.4383        | 26.84 | 108  | 0.1107          | 0.9538   |
| 0.4383        | 27.84 | 112  | 0.1237          | 0.9385   |
| 0.4383        | 28.84 | 116  | 0.1366          | 0.9538   |
| 0.4149        | 29.84 | 120  | 0.1349          | 0.9692   |
| 0.4149        | 30.84 | 124  | 0.1046          | 0.9846   |
| 0.4149        | 31.84 | 128  | 0.0882          | 0.9846   |
| 0.4149        | 32.84 | 132  | 0.1022          | 0.9846   |
| 0.4149        | 33.84 | 136  | 0.1207          | 0.9692   |
| 0.3657        | 34.84 | 140  | 0.1168          | 0.9538   |
| 0.3657        | 35.84 | 144  | 0.0922          | 0.9846   |
| 0.3657        | 36.84 | 148  | 0.0931          | 0.9846   |
| 0.3657        | 37.84 | 152  | 0.1006          | 0.9692   |
| 0.3657        | 38.84 | 156  | 0.0987          | 0.9692   |
| 0.3294        | 39.84 | 160  | 0.1128          | 0.9692   |
| 0.3294        | 40.84 | 164  | 0.1152          | 0.9538   |
| 0.3294        | 41.84 | 168  | 0.0997          | 0.9538   |
| 0.3294        | 42.84 | 172  | 0.0968          | 0.9692   |
| 0.3294        | 43.84 | 176  | 0.0819          | 0.9846   |
| 0.3198        | 44.84 | 180  | 0.0729          | 0.9846   |
| 0.3198        | 45.84 | 184  | 0.0744          | 0.9846   |
| 0.3198        | 46.84 | 188  | 0.0951          | 0.9692   |
| 0.3198        | 47.84 | 192  | 0.0966          | 0.9692   |
| 0.3198        | 48.84 | 196  | 0.0833          | 0.9846   |
| 0.2936        | 49.84 | 200  | 0.0694          | 0.9846   |
| 0.2936        | 50.84 | 204  | 0.0691          | 0.9846   |
| 0.2936        | 51.84 | 208  | 0.0736          | 0.9846   |
| 0.2936        | 52.84 | 212  | 0.0805          | 0.9692   |
| 0.2936        | 53.84 | 216  | 0.0801          | 0.9846   |
| 0.3127        | 54.84 | 220  | 0.0826          | 0.9846   |
| 0.3127        | 55.84 | 224  | 0.0857          | 0.9692   |
| 0.3127        | 56.84 | 228  | 0.0864          | 0.9846   |
| 0.3127        | 57.84 | 232  | 0.0878          | 0.9846   |
| 0.3127        | 58.84 | 236  | 0.0877          | 0.9846   |
| 0.285         | 59.84 | 240  | 0.0874          | 0.9846   |


### Framework versions

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