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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: 0.9692307692307692
---
<!-- 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: 0.2293
- Accuracy: 0.9692
## 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: 60
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.84 | 4 | 1.9335 | 0.1846 |
| No log | 1.84 | 8 | 1.8364 | 0.2615 |
| No log | 2.84 | 12 | 1.7054 | 0.3846 |
| No log | 3.84 | 16 | 1.5629 | 0.4154 |
| 2.0106 | 4.84 | 20 | 1.3907 | 0.4769 |
| 2.0106 | 5.84 | 24 | 1.1984 | 0.5692 |
| 2.0106 | 6.84 | 28 | 0.9519 | 0.6615 |
| 2.0106 | 7.84 | 32 | 0.7510 | 0.7846 |
| 2.0106 | 8.84 | 36 | 0.5749 | 0.8615 |
| 1.1009 | 9.84 | 40 | 0.4244 | 0.9385 |
| 1.1009 | 10.84 | 44 | 0.3652 | 0.8923 |
| 1.1009 | 11.84 | 48 | 0.2735 | 0.9538 |
| 1.1009 | 12.84 | 52 | 0.2909 | 0.8923 |
| 1.1009 | 13.84 | 56 | 0.2293 | 0.9692 |
| 0.6329 | 14.84 | 60 | 0.2563 | 0.9077 |
| 0.6329 | 15.84 | 64 | 0.2218 | 0.9231 |
| 0.6329 | 16.84 | 68 | 0.2102 | 0.9538 |
| 0.6329 | 17.84 | 72 | 0.1829 | 0.9231 |
| 0.6329 | 18.84 | 76 | 0.1992 | 0.9231 |
| 0.497 | 19.84 | 80 | 0.1814 | 0.9231 |
| 0.497 | 20.84 | 84 | 0.1807 | 0.9385 |
| 0.497 | 21.84 | 88 | 0.1765 | 0.9538 |
| 0.497 | 22.84 | 92 | 0.1868 | 0.9231 |
| 0.497 | 23.84 | 96 | 0.2089 | 0.9385 |
| 0.4198 | 24.84 | 100 | 0.1898 | 0.9385 |
| 0.4198 | 25.84 | 104 | 0.2065 | 0.9231 |
| 0.4198 | 26.84 | 108 | 0.1845 | 0.9231 |
| 0.4198 | 27.84 | 112 | 0.1724 | 0.9231 |
| 0.4198 | 28.84 | 116 | 0.1612 | 0.9385 |
| 0.368 | 29.84 | 120 | 0.1538 | 0.9538 |
| 0.368 | 30.84 | 124 | 0.1568 | 0.9538 |
| 0.368 | 31.84 | 128 | 0.1475 | 0.9692 |
| 0.368 | 32.84 | 132 | 0.1453 | 0.9538 |
| 0.368 | 33.84 | 136 | 0.1576 | 0.9692 |
| 0.3709 | 34.84 | 140 | 0.1430 | 0.9692 |
| 0.3709 | 35.84 | 144 | 0.1384 | 0.9692 |
| 0.3709 | 36.84 | 148 | 0.1432 | 0.9692 |
| 0.3709 | 37.84 | 152 | 0.1347 | 0.9692 |
| 0.3709 | 38.84 | 156 | 0.1359 | 0.9538 |
| 0.3373 | 39.84 | 160 | 0.1597 | 0.9538 |
| 0.3373 | 40.84 | 164 | 0.1522 | 0.9692 |
| 0.3373 | 41.84 | 168 | 0.1477 | 0.9538 |
| 0.3373 | 42.84 | 172 | 0.1480 | 0.9692 |
| 0.3373 | 43.84 | 176 | 0.1472 | 0.9692 |
| 0.3342 | 44.84 | 180 | 0.1473 | 0.9692 |
| 0.3342 | 45.84 | 184 | 0.1458 | 0.9692 |
| 0.3342 | 46.84 | 188 | 0.1529 | 0.9692 |
| 0.3342 | 47.84 | 192 | 0.1550 | 0.9692 |
| 0.3342 | 48.84 | 196 | 0.1494 | 0.9692 |
| 0.2914 | 49.84 | 200 | 0.1470 | 0.9692 |
| 0.2914 | 50.84 | 204 | 0.1460 | 0.9692 |
| 0.2914 | 51.84 | 208 | 0.1478 | 0.9692 |
| 0.2914 | 52.84 | 212 | 0.1481 | 0.9692 |
| 0.2914 | 53.84 | 216 | 0.1461 | 0.9692 |
| 0.2736 | 54.84 | 220 | 0.1458 | 0.9692 |
| 0.2736 | 55.84 | 224 | 0.1438 | 0.9692 |
| 0.2736 | 56.84 | 228 | 0.1427 | 0.9692 |
| 0.2736 | 57.84 | 232 | 0.1418 | 0.9692 |
| 0.2736 | 58.84 | 236 | 0.1401 | 0.9692 |
| 0.2589 | 59.84 | 240 | 0.1399 | 0.9692 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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