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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-bottomCleanedData
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: 0.9931895573212258
---
<!-- 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-bottomCleanedData
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: 0.0238
- Accuracy: 0.9932
## 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: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3257 | 1.0 | 141 | 0.2017 | 0.9330 |
| 0.2234 | 2.0 | 283 | 0.0655 | 0.9773 |
| 0.2719 | 2.99 | 424 | 0.0542 | 0.9773 |
| 0.1726 | 4.0 | 566 | 0.0446 | 0.9818 |
| 0.2053 | 4.99 | 707 | 0.0373 | 0.9864 |
| 0.1794 | 6.0 | 849 | 0.0413 | 0.9864 |
| 0.1645 | 7.0 | 991 | 0.0446 | 0.9818 |
| 0.1445 | 8.0 | 1132 | 0.0238 | 0.9932 |
| 0.1469 | 9.0 | 1274 | 0.0252 | 0.9909 |
| 0.0931 | 9.96 | 1410 | 0.0236 | 0.9921 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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