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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-uploads-classifier-v2
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: 0.984313725490196
---
<!-- 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-uploads-classifier-v2
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: 0.0745
- Accuracy: 0.9843
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2482 | 1.0 | 18 | 0.4781 | 0.8824 |
| 0.3036 | 2.0 | 36 | 0.0936 | 0.9804 |
| 0.1687 | 3.0 | 54 | 0.0745 | 0.9843 |
| 0.1392 | 4.0 | 72 | 0.0980 | 0.9725 |
| 0.14 | 5.0 | 90 | 0.0778 | 0.9765 |
| 0.1186 | 6.0 | 108 | 0.0837 | 0.9725 |
| 0.1088 | 7.0 | 126 | 0.0645 | 0.9804 |
| 0.0789 | 8.0 | 144 | 0.0675 | 0.9765 |
| 0.0644 | 9.0 | 162 | 0.0940 | 0.9686 |
| 0.0582 | 10.0 | 180 | 0.0879 | 0.9725 |
| 0.0591 | 11.0 | 198 | 0.0935 | 0.9686 |
| 0.0538 | 12.0 | 216 | 0.0540 | 0.9804 |
| 0.0588 | 13.0 | 234 | 0.0725 | 0.9686 |
| 0.0538 | 14.0 | 252 | 0.0637 | 0.9765 |
| 0.0462 | 15.0 | 270 | 0.0694 | 0.9725 |
| 0.0352 | 16.0 | 288 | 0.0771 | 0.9686 |
| 0.0536 | 17.0 | 306 | 0.0629 | 0.9804 |
| 0.0403 | 18.0 | 324 | 0.0933 | 0.9686 |
| 0.0412 | 19.0 | 342 | 0.0848 | 0.9725 |
| 0.0305 | 20.0 | 360 | 0.0820 | 0.9725 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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