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---
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-teeth_dataset
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: 0.8391304347826087
---
<!-- 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-teeth_dataset
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: 1.0631
- Accuracy: 0.8391
## 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.8 | 3 | 4.5796 | 0.0152 |
| No log | 1.87 | 7 | 4.5200 | 0.0261 |
| 4.5616 | 2.93 | 11 | 4.4705 | 0.0326 |
| 4.5616 | 4.0 | 15 | 4.4127 | 0.0674 |
| 4.5616 | 4.8 | 18 | 4.3493 | 0.0804 |
| 4.44 | 5.87 | 22 | 4.2425 | 0.1130 |
| 4.44 | 6.93 | 26 | 4.1107 | 0.1370 |
| 4.1823 | 8.0 | 30 | 3.9340 | 0.1609 |
| 4.1823 | 8.8 | 33 | 3.7821 | 0.1935 |
| 4.1823 | 9.87 | 37 | 3.5314 | 0.2783 |
| 3.6357 | 10.93 | 41 | 3.2857 | 0.3043 |
| 3.6357 | 12.0 | 45 | 3.1064 | 0.3696 |
| 3.6357 | 12.8 | 48 | 2.9713 | 0.3826 |
| 3.0041 | 13.87 | 52 | 2.7172 | 0.4870 |
| 3.0041 | 14.93 | 56 | 2.5111 | 0.5435 |
| 2.4604 | 16.0 | 60 | 2.3561 | 0.5696 |
| 2.4604 | 16.8 | 63 | 2.2684 | 0.5717 |
| 2.4604 | 17.87 | 67 | 2.0961 | 0.6348 |
| 1.971 | 18.93 | 71 | 1.9555 | 0.6783 |
| 1.971 | 20.0 | 75 | 1.8400 | 0.6891 |
| 1.971 | 20.8 | 78 | 1.7856 | 0.7239 |
| 1.651 | 21.87 | 82 | 1.6797 | 0.7370 |
| 1.651 | 22.93 | 86 | 1.6007 | 0.7717 |
| 1.3665 | 24.0 | 90 | 1.5256 | 0.7739 |
| 1.3665 | 24.8 | 93 | 1.4876 | 0.7652 |
| 1.3665 | 25.87 | 97 | 1.4395 | 0.7783 |
| 1.1954 | 26.93 | 101 | 1.3679 | 0.7870 |
| 1.1954 | 28.0 | 105 | 1.3043 | 0.8022 |
| 1.1954 | 28.8 | 108 | 1.2906 | 0.8022 |
| 0.9886 | 29.87 | 112 | 1.2313 | 0.8109 |
| 0.9886 | 30.93 | 116 | 1.1829 | 0.8348 |
| 0.8803 | 32.0 | 120 | 1.1564 | 0.8391 |
| 0.8803 | 32.8 | 123 | 1.1421 | 0.8304 |
| 0.8803 | 33.87 | 127 | 1.1144 | 0.8326 |
| 0.815 | 34.93 | 131 | 1.1074 | 0.8304 |
| 0.815 | 36.0 | 135 | 1.0919 | 0.8283 |
| 0.815 | 36.8 | 138 | 1.0821 | 0.8326 |
| 0.7619 | 37.87 | 142 | 1.0701 | 0.8348 |
| 0.7619 | 38.93 | 146 | 1.0642 | 0.8348 |
| 0.6991 | 40.0 | 150 | 1.0631 | 0.8391 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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