---
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 [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: 0.0038
- 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        | 1.0   | 3    | 0.1626          | 0.95     |
| No log        | 2.0   | 6    | 0.1593          | 0.95     |
| No log        | 3.0   | 9    | 0.1342          | 0.95     |
| No log        | 4.0   | 12   | 0.0871          | 0.975    |
| No log        | 5.0   | 15   | 0.0612          | 0.975    |
| No log        | 6.0   | 18   | 0.0431          | 1.0      |
| 0.2745        | 7.0   | 21   | 0.0333          | 1.0      |
| 0.2745        | 8.0   | 24   | 0.0487          | 1.0      |
| 0.2745        | 9.0   | 27   | 0.0456          | 1.0      |
| 0.2745        | 10.0  | 30   | 0.0273          | 1.0      |
| 0.2745        | 11.0  | 33   | 0.0180          | 1.0      |
| 0.2745        | 12.0  | 36   | 0.0168          | 1.0      |
| 0.2745        | 13.0  | 39   | 0.0310          | 1.0      |
| 0.1782        | 14.0  | 42   | 0.0438          | 0.975    |
| 0.1782        | 15.0  | 45   | 0.0750          | 0.975    |
| 0.1782        | 16.0  | 48   | 0.0396          | 0.975    |
| 0.1782        | 17.0  | 51   | 0.0177          | 1.0      |
| 0.1782        | 18.0  | 54   | 0.0217          | 1.0      |
| 0.1782        | 19.0  | 57   | 0.0116          | 1.0      |
| 0.1624        | 20.0  | 60   | 0.0081          | 1.0      |
| 0.1624        | 21.0  | 63   | 0.0066          | 1.0      |
| 0.1624        | 22.0  | 66   | 0.0083          | 1.0      |
| 0.1624        | 23.0  | 69   | 0.0126          | 1.0      |
| 0.1624        | 24.0  | 72   | 0.0158          | 1.0      |
| 0.1624        | 25.0  | 75   | 0.0188          | 1.0      |
| 0.1624        | 26.0  | 78   | 0.0149          | 1.0      |
| 0.1475        | 27.0  | 81   | 0.0101          | 1.0      |
| 0.1475        | 28.0  | 84   | 0.0064          | 1.0      |
| 0.1475        | 29.0  | 87   | 0.0050          | 1.0      |
| 0.1475        | 30.0  | 90   | 0.0052          | 1.0      |
| 0.1475        | 31.0  | 93   | 0.0064          | 1.0      |
| 0.1475        | 32.0  | 96   | 0.0070          | 1.0      |
| 0.1475        | 33.0  | 99   | 0.0069          | 1.0      |
| 0.1345        | 34.0  | 102  | 0.0059          | 1.0      |
| 0.1345        | 35.0  | 105  | 0.0049          | 1.0      |
| 0.1345        | 36.0  | 108  | 0.0043          | 1.0      |
| 0.1345        | 37.0  | 111  | 0.0040          | 1.0      |
| 0.1345        | 38.0  | 114  | 0.0038          | 1.0      |
| 0.1345        | 39.0  | 117  | 0.0038          | 1.0      |
| 0.1232        | 40.0  | 120  | 0.0038          | 1.0      |


### Framework versions

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