---
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