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---
license: apache-2.0
base_model: Dhyey8/swin-tiny-patch4-window7-224-finetuned-teeth_dataset
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-teeth_dataset-finetuned-teeth_dataset-V2
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: 0.9260869565217391
---
<!-- 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-finetuned-teeth_dataset-V2
This model is a fine-tuned version of [Dhyey8/swin-tiny-patch4-window7-224-finetuned-teeth_dataset](https://huggingface.co/Dhyey8/swin-tiny-patch4-window7-224-finetuned-teeth_dataset) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3081
- Accuracy: 0.9261
## 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 | 1.1267 | 0.8391 |
| No log | 1.87 | 7 | 1.0719 | 0.8304 |
| 0.5709 | 2.93 | 11 | 0.9447 | 0.8478 |
| 0.5709 | 4.0 | 15 | 0.8442 | 0.8652 |
| 0.5709 | 4.8 | 18 | 0.7065 | 0.8826 |
| 0.3317 | 5.87 | 22 | 0.6930 | 0.8891 |
| 0.3317 | 6.93 | 26 | 0.5630 | 0.8978 |
| 0.1576 | 8.0 | 30 | 0.5882 | 0.8826 |
| 0.1576 | 8.8 | 33 | 0.5198 | 0.9087 |
| 0.1576 | 9.87 | 37 | 0.4425 | 0.9043 |
| 0.0883 | 10.93 | 41 | 0.4727 | 0.8978 |
| 0.0883 | 12.0 | 45 | 0.4314 | 0.9022 |
| 0.0883 | 12.8 | 48 | 0.4011 | 0.9022 |
| 0.051 | 13.87 | 52 | 0.4045 | 0.9174 |
| 0.051 | 14.93 | 56 | 0.3745 | 0.9109 |
| 0.0415 | 16.0 | 60 | 0.3597 | 0.9152 |
| 0.0415 | 16.8 | 63 | 0.4016 | 0.9065 |
| 0.0415 | 17.87 | 67 | 0.3804 | 0.9152 |
| 0.0307 | 18.93 | 71 | 0.3519 | 0.9217 |
| 0.0307 | 20.0 | 75 | 0.4131 | 0.8935 |
| 0.0307 | 20.8 | 78 | 0.4047 | 0.9 |
| 0.0262 | 21.87 | 82 | 0.3450 | 0.9174 |
| 0.0262 | 22.93 | 86 | 0.3639 | 0.9109 |
| 0.0208 | 24.0 | 90 | 0.3843 | 0.9043 |
| 0.0208 | 24.8 | 93 | 0.3797 | 0.8978 |
| 0.0208 | 25.87 | 97 | 0.3660 | 0.9152 |
| 0.0141 | 26.93 | 101 | 0.3445 | 0.9152 |
| 0.0141 | 28.0 | 105 | 0.3131 | 0.9239 |
| 0.0141 | 28.8 | 108 | 0.3069 | 0.9196 |
| 0.0114 | 29.87 | 112 | 0.3006 | 0.9196 |
| 0.0114 | 30.93 | 116 | 0.3097 | 0.9239 |
| 0.014 | 32.0 | 120 | 0.3121 | 0.9174 |
| 0.014 | 32.8 | 123 | 0.3242 | 0.9174 |
| 0.014 | 33.87 | 127 | 0.3291 | 0.9217 |
| 0.016 | 34.93 | 131 | 0.3156 | 0.9217 |
| 0.016 | 36.0 | 135 | 0.3081 | 0.9261 |
| 0.016 | 36.8 | 138 | 0.3084 | 0.9261 |
| 0.0114 | 37.87 | 142 | 0.3148 | 0.9196 |
| 0.0114 | 38.93 | 146 | 0.3191 | 0.9174 |
| 0.0091 | 40.0 | 150 | 0.3191 | 0.9174 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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