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---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-vit0
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: 0.8314176245210728
---
<!-- 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-tiny-patch4-window7-224-vit0
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: 0.4836
- Accuracy: 0.8314
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.13 | 0.97 | 18 | 1.0297 | 0.4330 |
| 0.9066 | 2.0 | 37 | 0.8349 | 0.6590 |
| 0.7157 | 2.97 | 55 | 0.8050 | 0.6743 |
| 0.6446 | 4.0 | 74 | 0.6934 | 0.7165 |
| 0.5707 | 4.97 | 92 | 0.6324 | 0.7433 |
| 0.5042 | 6.0 | 111 | 0.6156 | 0.7356 |
| 0.4714 | 6.97 | 129 | 0.6825 | 0.7241 |
| 0.4225 | 8.0 | 148 | 0.5692 | 0.7625 |
| 0.3912 | 8.97 | 166 | 0.6150 | 0.7586 |
| 0.3442 | 10.0 | 185 | 0.4901 | 0.8008 |
| 0.289 | 10.97 | 203 | 0.5580 | 0.7739 |
| 0.2827 | 12.0 | 222 | 0.5308 | 0.7969 |
| 0.2375 | 12.97 | 240 | 0.5274 | 0.8046 |
| 0.2493 | 14.0 | 259 | 0.5433 | 0.8046 |
| 0.2309 | 14.97 | 277 | 0.5355 | 0.7931 |
| 0.1963 | 16.0 | 296 | 0.4836 | 0.8314 |
| 0.2162 | 16.97 | 314 | 0.4973 | 0.8238 |
| 0.2256 | 18.0 | 333 | 0.4918 | 0.8276 |
| 0.2124 | 18.97 | 351 | 0.5071 | 0.8161 |
| 0.1797 | 19.46 | 360 | 0.4985 | 0.8199 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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