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---
library_name: transformers
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-finetuned-papsmear
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: 0.8970588235294118
---
<!-- 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-papsmear
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: 0.3057
- Accuracy: 0.8971
## 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: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.4898 | 0.9935 | 38 | 1.3709 | 0.4632 |
| 0.8902 | 1.9869 | 76 | 0.9261 | 0.6324 |
| 0.9107 | 2.9804 | 114 | 0.8400 | 0.6397 |
| 0.564 | 4.0 | 153 | 0.6937 | 0.7279 |
| 0.5563 | 4.9935 | 191 | 0.5622 | 0.7647 |
| 0.3851 | 5.9869 | 229 | 0.5238 | 0.8015 |
| 0.3327 | 6.9804 | 267 | 0.6382 | 0.7941 |
| 0.2469 | 8.0 | 306 | 0.4330 | 0.8456 |
| 0.2903 | 8.9935 | 344 | 0.4212 | 0.8309 |
| 0.1861 | 9.9869 | 382 | 0.4140 | 0.8529 |
| 0.1533 | 10.9804 | 420 | 0.3810 | 0.8603 |
| 0.1017 | 12.0 | 459 | 0.3565 | 0.8603 |
| 0.1285 | 12.9935 | 497 | 0.3057 | 0.8971 |
| 0.1377 | 13.9869 | 535 | 0.3058 | 0.8824 |
| 0.1033 | 14.9020 | 570 | 0.3140 | 0.8824 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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