---
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: 0.9555555555555556
---

<!-- 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: 0.2060
- Accuracy: 0.9556

## 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        | 0.92  | 3    | 0.3269          | 0.9111   |
| No log        | 1.92  | 6    | 0.2814          | 0.9333   |
| No log        | 2.92  | 9    | 0.2625          | 0.9333   |
| No log        | 3.92  | 12   | 0.2771          | 0.9333   |
| No log        | 4.92  | 15   | 0.2419          | 0.9333   |
| No log        | 5.92  | 18   | 0.2264          | 0.9111   |
| 0.3207        | 6.92  | 21   | 0.2530          | 0.9333   |
| 0.3207        | 7.92  | 24   | 0.2242          | 0.9333   |
| 0.3207        | 8.92  | 27   | 0.2060          | 0.9556   |
| 0.3207        | 9.92  | 30   | 0.1809          | 0.9556   |
| 0.3207        | 10.92 | 33   | 0.2070          | 0.9556   |
| 0.3207        | 11.92 | 36   | 0.1999          | 0.9556   |
| 0.3207        | 12.92 | 39   | 0.2013          | 0.9556   |
| 0.2066        | 13.92 | 42   | 0.2027          | 0.9556   |
| 0.2066        | 14.92 | 45   | 0.1809          | 0.9556   |
| 0.2066        | 15.92 | 48   | 0.1657          | 0.9556   |
| 0.2066        | 16.92 | 51   | 0.1728          | 0.9556   |
| 0.2066        | 17.92 | 54   | 0.2013          | 0.9556   |
| 0.2066        | 18.92 | 57   | 0.2226          | 0.9556   |
| 0.1894        | 19.92 | 60   | 0.2091          | 0.9556   |
| 0.1894        | 20.92 | 63   | 0.1940          | 0.9556   |
| 0.1894        | 21.92 | 66   | 0.1976          | 0.9556   |
| 0.1894        | 22.92 | 69   | 0.2232          | 0.9556   |
| 0.1894        | 23.92 | 72   | 0.2381          | 0.9556   |
| 0.1894        | 24.92 | 75   | 0.2405          | 0.9556   |
| 0.1894        | 25.92 | 78   | 0.2247          | 0.9556   |
| 0.1713        | 26.92 | 81   | 0.1895          | 0.9556   |
| 0.1713        | 27.92 | 84   | 0.1836          | 0.9556   |
| 0.1713        | 28.92 | 87   | 0.1985          | 0.9556   |
| 0.1713        | 29.92 | 90   | 0.2127          | 0.9556   |
| 0.1713        | 30.92 | 93   | 0.2098          | 0.9556   |
| 0.1713        | 31.92 | 96   | 0.2003          | 0.9556   |
| 0.1713        | 32.92 | 99   | 0.1849          | 0.9556   |
| 0.1428        | 33.92 | 102  | 0.1843          | 0.9556   |
| 0.1428        | 34.92 | 105  | 0.1900          | 0.9556   |
| 0.1428        | 35.92 | 108  | 0.1972          | 0.9556   |
| 0.1428        | 36.92 | 111  | 0.2023          | 0.9556   |
| 0.1428        | 37.92 | 114  | 0.2060          | 0.9556   |
| 0.1428        | 38.92 | 117  | 0.2093          | 0.9556   |
| 0.1443        | 39.92 | 120  | 0.2106          | 0.9556   |


### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1