---
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: 0.9714285714285714
---

<!-- 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 [JEdward7777/delivery_truck_classification](https://huggingface.co/JEdward7777/delivery_truck_classification) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2074
- Accuracy: 0.9714

## 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   | 2    | 0.1919          | 0.9429   |
| No log        | 1.8   | 4    | 0.1383          | 0.9714   |
| No log        | 2.8   | 6    | 0.1930          | 0.9143   |
| No log        | 3.8   | 8    | 0.1463          | 0.9714   |
| No log        | 4.8   | 10   | 0.1735          | 0.9714   |
| No log        | 5.8   | 12   | 0.1692          | 0.9714   |
| No log        | 6.8   | 14   | 0.1626          | 0.9714   |
| No log        | 7.8   | 16   | 0.1659          | 0.9714   |
| No log        | 8.8   | 18   | 0.1622          | 0.9714   |
| 0.2046        | 9.8   | 20   | 0.1598          | 0.9714   |
| 0.2046        | 10.8  | 22   | 0.1668          | 0.9714   |
| 0.2046        | 11.8  | 24   | 0.1747          | 0.9714   |
| 0.2046        | 12.8  | 26   | 0.1804          | 0.9714   |
| 0.2046        | 13.8  | 28   | 0.1837          | 0.9714   |
| 0.2046        | 14.8  | 30   | 0.1837          | 0.9714   |
| 0.2046        | 15.8  | 32   | 0.1811          | 0.9714   |
| 0.2046        | 16.8  | 34   | 0.1801          | 0.9714   |
| 0.2046        | 17.8  | 36   | 0.1841          | 0.9714   |
| 0.2046        | 18.8  | 38   | 0.1899          | 0.9714   |
| 0.1657        | 19.8  | 40   | 0.1960          | 0.9714   |
| 0.1657        | 20.8  | 42   | 0.1993          | 0.9714   |
| 0.1657        | 21.8  | 44   | 0.2017          | 0.9714   |
| 0.1657        | 22.8  | 46   | 0.2004          | 0.9714   |
| 0.1657        | 23.8  | 48   | 0.1922          | 0.9714   |
| 0.1657        | 24.8  | 50   | 0.1856          | 0.9714   |
| 0.1657        | 25.8  | 52   | 0.1834          | 0.9714   |
| 0.1657        | 26.8  | 54   | 0.1846          | 0.9714   |
| 0.1657        | 27.8  | 56   | 0.1898          | 0.9714   |
| 0.1657        | 28.8  | 58   | 0.1951          | 0.9714   |
| 0.1308        | 29.8  | 60   | 0.2019          | 0.9714   |
| 0.1308        | 30.8  | 62   | 0.2095          | 0.9714   |
| 0.1308        | 31.8  | 64   | 0.2145          | 0.9714   |
| 0.1308        | 32.8  | 66   | 0.2154          | 0.9714   |
| 0.1308        | 33.8  | 68   | 0.2137          | 0.9714   |
| 0.1308        | 34.8  | 70   | 0.2116          | 0.9714   |
| 0.1308        | 35.8  | 72   | 0.2096          | 0.9714   |
| 0.1308        | 36.8  | 74   | 0.2084          | 0.9714   |
| 0.1308        | 37.8  | 76   | 0.2078          | 0.9714   |
| 0.1308        | 38.8  | 78   | 0.2075          | 0.9714   |
| 0.1053        | 39.8  | 80   | 0.2074          | 0.9714   |


### Framework versions

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