|
--- |
|
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: 0.1787 |
|
- 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 | 0.8 | 1 | 2.0794 | 0.0588 | |
|
| No log | 1.8 | 2 | 2.0047 | 0.1176 | |
|
| No log | 2.8 | 3 | 1.8666 | 0.1765 | |
|
| No log | 3.8 | 4 | 1.6800 | 0.2353 | |
|
| No log | 4.8 | 5 | 1.4622 | 0.3529 | |
|
| No log | 5.8 | 6 | 1.2880 | 0.5882 | |
|
| No log | 6.8 | 7 | 1.1316 | 0.8824 | |
|
| No log | 7.8 | 8 | 0.9925 | 0.8824 | |
|
| No log | 8.8 | 9 | 0.8822 | 0.8824 | |
|
| No log | 9.8 | 10 | 0.7928 | 0.8824 | |
|
| No log | 10.8 | 11 | 0.7266 | 0.8824 | |
|
| No log | 11.8 | 12 | 0.6715 | 0.8824 | |
|
| No log | 12.8 | 13 | 0.6238 | 0.8824 | |
|
| No log | 13.8 | 14 | 0.5793 | 0.8824 | |
|
| No log | 14.8 | 15 | 0.5423 | 0.8824 | |
|
| No log | 15.8 | 16 | 0.5103 | 0.8824 | |
|
| No log | 16.8 | 17 | 0.4865 | 0.9412 | |
|
| No log | 17.8 | 18 | 0.4635 | 0.9412 | |
|
| No log | 18.8 | 19 | 0.4399 | 0.9412 | |
|
| 1.3142 | 19.8 | 20 | 0.4119 | 0.9412 | |
|
| 1.3142 | 20.8 | 21 | 0.3843 | 0.9412 | |
|
| 1.3142 | 21.8 | 22 | 0.3497 | 0.9412 | |
|
| 1.3142 | 22.8 | 23 | 0.3161 | 0.9412 | |
|
| 1.3142 | 23.8 | 24 | 0.2850 | 0.9412 | |
|
| 1.3142 | 24.8 | 25 | 0.2581 | 0.9412 | |
|
| 1.3142 | 25.8 | 26 | 0.2363 | 0.9412 | |
|
| 1.3142 | 26.8 | 27 | 0.2179 | 0.9412 | |
|
| 1.3142 | 27.8 | 28 | 0.2029 | 0.9412 | |
|
| 1.3142 | 28.8 | 29 | 0.1903 | 0.9412 | |
|
| 1.3142 | 29.8 | 30 | 0.1787 | 1.0 | |
|
| 1.3142 | 30.8 | 31 | 0.1676 | 1.0 | |
|
| 1.3142 | 31.8 | 32 | 0.1581 | 1.0 | |
|
| 1.3142 | 32.8 | 33 | 0.1487 | 1.0 | |
|
| 1.3142 | 33.8 | 34 | 0.1410 | 1.0 | |
|
| 1.3142 | 34.8 | 35 | 0.1349 | 1.0 | |
|
| 1.3142 | 35.8 | 36 | 0.1301 | 1.0 | |
|
| 1.3142 | 36.8 | 37 | 0.1266 | 1.0 | |
|
| 1.3142 | 37.8 | 38 | 0.1243 | 1.0 | |
|
| 1.3142 | 38.8 | 39 | 0.1230 | 1.0 | |
|
| 0.4316 | 39.8 | 40 | 0.1223 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.2 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
