|
--- |
|
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 |
|
|
