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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-arty
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: 1.0
---
<!-- 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-finetuned-arty
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: 0.0002
- Accuracy: 1.0
## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2386 | 0.43 | 50 | 0.0643 | 0.9967 |
| 0.0359 | 0.87 | 100 | 0.0035 | 0.9996 |
| 0.058 | 1.3 | 150 | 0.0015 | 0.9996 |
| 0.0297 | 1.74 | 200 | 0.0003 | 1.0 |
| 0.0175 | 2.17 | 250 | 0.0002 | 1.0 |
| 0.0166 | 2.6 | 300 | 0.0002 | 1.0 |
| 0.0318 | 3.04 | 350 | 0.0001 | 1.0 |
| 0.0062 | 3.47 | 400 | 0.0002 | 1.0 |
| 0.0101 | 3.9 | 450 | 0.0002 | 1.0 |
| 0.0066 | 4.34 | 500 | 0.0002 | 1.0 |
| 0.005 | 4.77 | 550 | 0.0002 | 1.0 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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