---
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: 0.0416
- 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        | 0.73  | 2    | 0.0416          | 1.0      |
| No log        | 1.73  | 4    | 0.0346          | 1.0      |
| No log        | 2.73  | 6    | 0.0293          | 1.0      |
| No log        | 3.73  | 8    | 0.0186          | 1.0      |
| No log        | 4.73  | 10   | 0.0205          | 1.0      |
| No log        | 5.73  | 12   | 0.0604          | 0.9730   |
| No log        | 6.73  | 14   | 0.0332          | 1.0      |
| No log        | 7.73  | 16   | 0.0250          | 1.0      |
| No log        | 8.73  | 18   | 0.0386          | 1.0      |
| 0.2483        | 9.73  | 20   | 0.0438          | 1.0      |
| 0.2483        | 10.73 | 22   | 0.0447          | 1.0      |
| 0.2483        | 11.73 | 24   | 0.0676          | 0.9730   |
| 0.2483        | 12.73 | 26   | 0.0786          | 0.9730   |
| 0.2483        | 13.73 | 28   | 0.0389          | 1.0      |
| 0.2483        | 14.73 | 30   | 0.0278          | 1.0      |
| 0.2483        | 15.73 | 32   | 0.0250          | 1.0      |
| 0.2483        | 16.73 | 34   | 0.0283          | 1.0      |
| 0.2483        | 17.73 | 36   | 0.0502          | 0.9730   |
| 0.2483        | 18.73 | 38   | 0.0711          | 0.9730   |
| 0.1759        | 19.73 | 40   | 0.0637          | 0.9730   |
| 0.1759        | 20.73 | 42   | 0.0459          | 1.0      |
| 0.1759        | 21.73 | 44   | 0.0394          | 1.0      |
| 0.1759        | 22.73 | 46   | 0.0419          | 1.0      |
| 0.1759        | 23.73 | 48   | 0.0423          | 1.0      |
| 0.1759        | 24.73 | 50   | 0.0463          | 0.9730   |
| 0.1759        | 25.73 | 52   | 0.0503          | 0.9730   |
| 0.1759        | 26.73 | 54   | 0.0616          | 0.9730   |
| 0.1759        | 27.73 | 56   | 0.0641          | 0.9730   |
| 0.1759        | 28.73 | 58   | 0.0529          | 0.9730   |
| 0.1669        | 29.73 | 60   | 0.0485          | 0.9730   |
| 0.1669        | 30.73 | 62   | 0.0465          | 0.9730   |
| 0.1669        | 31.73 | 64   | 0.0456          | 0.9730   |
| 0.1669        | 32.73 | 66   | 0.0478          | 0.9730   |
| 0.1669        | 33.73 | 68   | 0.0467          | 0.9730   |
| 0.1669        | 34.73 | 70   | 0.0473          | 0.9730   |
| 0.1669        | 35.73 | 72   | 0.0486          | 0.9730   |
| 0.1669        | 36.73 | 74   | 0.0500          | 0.9730   |
| 0.1669        | 37.73 | 76   | 0.0502          | 0.9730   |
| 0.1669        | 38.73 | 78   | 0.0500          | 0.9730   |
| 0.1589        | 39.73 | 80   | 0.0493          | 0.9730   |


### Framework versions

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