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---
license: apache-2.0
base_model: mansee/swin-tiny-patch4-window7-224-blank_img
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-blank_img
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: 0.9738372093023255
---
<!-- 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-blank_img
This model is a fine-tuned version of [mansee/swin-tiny-patch4-window7-224-blank_img](https://huggingface.co./mansee/swin-tiny-patch4-window7-224-blank_img) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1016
- Accuracy: 0.9738
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0502 | 0.99 | 72 | 0.1300 | 0.9651 |
| 0.1107 | 1.99 | 145 | 0.1023 | 0.9729 |
| 0.0917 | 3.0 | 218 | 0.1277 | 0.9651 |
| 0.1022 | 4.0 | 291 | 0.1258 | 0.9719 |
| 0.0888 | 4.95 | 360 | 0.1016 | 0.9738 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|