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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: 0.9491525423728814
---
<!-- 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: 0.1253
- Accuracy: 0.9492
## 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 | 0.94 | 4 | 1.8882 | 0.1186 |
| No log | 1.94 | 8 | 1.6799 | 0.3559 |
| No log | 2.94 | 12 | 1.4260 | 0.5763 |
| No log | 3.94 | 16 | 1.1092 | 0.6780 |
| 1.7242 | 4.94 | 20 | 0.8653 | 0.7458 |
| 1.7242 | 5.94 | 24 | 0.6787 | 0.7797 |
| 1.7242 | 6.94 | 28 | 0.5506 | 0.8305 |
| 1.7242 | 7.94 | 32 | 0.4174 | 0.8814 |
| 1.7242 | 8.94 | 36 | 0.3643 | 0.8814 |
| 0.8337 | 9.94 | 40 | 0.2680 | 0.9322 |
| 0.8337 | 10.94 | 44 | 0.2705 | 0.8983 |
| 0.8337 | 11.94 | 48 | 0.2270 | 0.9153 |
| 0.8337 | 12.94 | 52 | 0.1790 | 0.9492 |
| 0.8337 | 13.94 | 56 | 0.1694 | 0.9322 |
| 0.493 | 14.94 | 60 | 0.1776 | 0.9153 |
| 0.493 | 15.94 | 64 | 0.1831 | 0.9322 |
| 0.493 | 16.94 | 68 | 0.1765 | 0.9322 |
| 0.493 | 17.94 | 72 | 0.1575 | 0.9322 |
| 0.493 | 18.94 | 76 | 0.1472 | 0.9322 |
| 0.3966 | 19.94 | 80 | 0.1360 | 0.9322 |
| 0.3966 | 20.94 | 84 | 0.1448 | 0.9492 |
| 0.3966 | 21.94 | 88 | 0.1658 | 0.9322 |
| 0.3966 | 22.94 | 92 | 0.1652 | 0.9322 |
| 0.3966 | 23.94 | 96 | 0.1565 | 0.9322 |
| 0.3645 | 24.94 | 100 | 0.1701 | 0.9322 |
| 0.3645 | 25.94 | 104 | 0.1830 | 0.9322 |
| 0.3645 | 26.94 | 108 | 0.1682 | 0.9322 |
| 0.3645 | 27.94 | 112 | 0.1410 | 0.9492 |
| 0.3645 | 28.94 | 116 | 0.1291 | 0.9492 |
| 0.3358 | 29.94 | 120 | 0.1248 | 0.9492 |
| 0.3358 | 30.94 | 124 | 0.1275 | 0.9492 |
| 0.3358 | 31.94 | 128 | 0.1257 | 0.9492 |
| 0.3358 | 32.94 | 132 | 0.1288 | 0.9492 |
| 0.3358 | 33.94 | 136 | 0.1246 | 0.9492 |
| 0.3049 | 34.94 | 140 | 0.1219 | 0.9492 |
| 0.3049 | 35.94 | 144 | 0.1224 | 0.9492 |
| 0.3049 | 36.94 | 148 | 0.1246 | 0.9492 |
| 0.3049 | 37.94 | 152 | 0.1243 | 0.9492 |
| 0.3049 | 38.94 | 156 | 0.1248 | 0.9492 |
| 0.2962 | 39.94 | 160 | 0.1253 | 0.9492 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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