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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 [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2180
- 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 | 0.57 | 1 | 1.7779 | 0.2727 |
| No log | 1.57 | 2 | 1.7088 | 0.3182 |
| No log | 2.57 | 3 | 1.5921 | 0.5455 |
| No log | 3.57 | 4 | 1.4587 | 0.5909 |
| No log | 4.57 | 5 | 1.3256 | 0.5455 |
| No log | 5.57 | 6 | 1.2211 | 0.5 |
| No log | 6.57 | 7 | 1.1066 | 0.6818 |
| No log | 7.57 | 8 | 0.9768 | 0.7727 |
| No log | 8.57 | 9 | 0.8590 | 0.8636 |
| No log | 9.57 | 10 | 0.7718 | 0.9091 |
| No log | 10.57 | 11 | 0.6999 | 0.9091 |
| No log | 11.57 | 12 | 0.6385 | 0.9091 |
| No log | 12.57 | 13 | 0.5761 | 0.9545 |
| No log | 13.57 | 14 | 0.5189 | 0.9545 |
| No log | 14.57 | 15 | 0.4646 | 0.9545 |
| No log | 15.57 | 16 | 0.4137 | 0.9091 |
| No log | 16.57 | 17 | 0.3679 | 0.9091 |
| No log | 17.57 | 18 | 0.3291 | 0.9091 |
| No log | 18.57 | 19 | 0.2937 | 0.9545 |
| 1.8863 | 19.57 | 20 | 0.2642 | 0.9545 |
| 1.8863 | 20.57 | 21 | 0.2366 | 0.9545 |
| 1.8863 | 21.57 | 22 | 0.2180 | 1.0 |
| 1.8863 | 22.57 | 23 | 0.2061 | 1.0 |
| 1.8863 | 23.57 | 24 | 0.1984 | 1.0 |
| 1.8863 | 24.57 | 25 | 0.1918 | 1.0 |
| 1.8863 | 25.57 | 26 | 0.1787 | 1.0 |
| 1.8863 | 26.57 | 27 | 0.1605 | 1.0 |
| 1.8863 | 27.57 | 28 | 0.1412 | 1.0 |
| 1.8863 | 28.57 | 29 | 0.1269 | 1.0 |
| 1.8863 | 29.57 | 30 | 0.1142 | 1.0 |
| 1.8863 | 30.57 | 31 | 0.1051 | 1.0 |
| 1.8863 | 31.57 | 32 | 0.0995 | 1.0 |
| 1.8863 | 32.57 | 33 | 0.0946 | 1.0 |
| 1.8863 | 33.57 | 34 | 0.0911 | 1.0 |
| 1.8863 | 34.57 | 35 | 0.0892 | 1.0 |
| 1.8863 | 35.57 | 36 | 0.0876 | 1.0 |
| 1.8863 | 36.57 | 37 | 0.0865 | 1.0 |
| 1.8863 | 37.57 | 38 | 0.0857 | 1.0 |
| 1.8863 | 38.57 | 39 | 0.0854 | 1.0 |
| 0.6775 | 39.57 | 40 | 0.0853 | 1.0 |
### Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cpu
- Datasets 2.4.0
- Tokenizers 0.12.1
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