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---
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
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