|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/swin-base-patch4-window7-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: swin-base-patch4-window7-224-finetuned-piid |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: val |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8127853881278538 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# swin-base-patch4-window7-224-finetuned-piid |
|
|
|
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6630 |
|
- Accuracy: 0.8128 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.1815 | 0.98 | 20 | 1.0441 | 0.5251 | |
|
| 0.6548 | 2.0 | 41 | 0.8150 | 0.6393 | |
|
| 0.6083 | 2.98 | 61 | 0.6395 | 0.6986 | |
|
| 0.4925 | 4.0 | 82 | 0.6273 | 0.6804 | |
|
| 0.4448 | 4.98 | 102 | 0.4812 | 0.8174 | |
|
| 0.3387 | 6.0 | 123 | 0.5868 | 0.7945 | |
|
| 0.2622 | 6.98 | 143 | 0.7868 | 0.7260 | |
|
| 0.2656 | 8.0 | 164 | 0.4432 | 0.8128 | |
|
| 0.2259 | 8.98 | 184 | 0.6553 | 0.7489 | |
|
| 0.1997 | 10.0 | 205 | 0.5143 | 0.7854 | |
|
| 0.1892 | 10.98 | 225 | 0.5657 | 0.7945 | |
|
| 0.1522 | 12.0 | 246 | 0.7339 | 0.7580 | |
|
| 0.1309 | 12.98 | 266 | 0.6064 | 0.8174 | |
|
| 0.1482 | 14.0 | 287 | 0.5875 | 0.8128 | |
|
| 0.1459 | 14.98 | 307 | 0.6443 | 0.7900 | |
|
| 0.1224 | 16.0 | 328 | 0.6521 | 0.8037 | |
|
| 0.0533 | 16.98 | 348 | 0.5915 | 0.8493 | |
|
| 0.1133 | 18.0 | 369 | 0.6152 | 0.8265 | |
|
| 0.0923 | 18.98 | 389 | 0.6819 | 0.7854 | |
|
| 0.086 | 19.51 | 400 | 0.6630 | 0.8128 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
