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---
license: apache-2.0
base_model: microsoft/swin-small-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-small-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: 0.776255707762557
---
<!-- 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-small-patch4-window7-224-finetuned-piid
This model is a fine-tuned version of [microsoft/swin-small-patch4-window7-224](https://huggingface.co/microsoft/swin-small-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6168
- Accuracy: 0.7763
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2327 | 0.98 | 20 | 1.1687 | 0.5114 |
| 0.7354 | 2.0 | 41 | 0.7696 | 0.6712 |
| 0.602 | 2.98 | 61 | 0.7198 | 0.7078 |
| 0.5809 | 4.0 | 82 | 0.5824 | 0.7397 |
| 0.4989 | 4.98 | 102 | 0.5331 | 0.7489 |
| 0.4364 | 6.0 | 123 | 0.6137 | 0.7489 |
| 0.3321 | 6.98 | 143 | 0.5839 | 0.7717 |
| 0.3 | 8.0 | 164 | 0.5246 | 0.7763 |
| 0.3024 | 8.98 | 184 | 0.5557 | 0.7717 |
| 0.3433 | 10.0 | 205 | 0.5258 | 0.7900 |
| 0.258 | 10.98 | 225 | 0.6354 | 0.7489 |
| 0.1595 | 12.0 | 246 | 0.5492 | 0.8219 |
| 0.2295 | 12.98 | 266 | 0.5889 | 0.7900 |
| 0.1956 | 14.0 | 287 | 0.5670 | 0.7900 |
| 0.2028 | 14.98 | 307 | 0.5460 | 0.7900 |
| 0.1514 | 16.0 | 328 | 0.6587 | 0.7900 |
| 0.0934 | 16.98 | 348 | 0.6131 | 0.7945 |
| 0.1323 | 18.0 | 369 | 0.6615 | 0.7900 |
| 0.1213 | 18.98 | 389 | 0.6192 | 0.7671 |
| 0.1028 | 19.51 | 400 | 0.6168 | 0.7763 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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