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---
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
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