| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: swinv2-tiny-patch4-window8-256-finetuned-thai |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: val |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.87375 |
| --- |
| |
| <!-- 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. --> |
|
|
| # swinv2-tiny-patch4-window8-256-finetuned-thai |
|
|
| This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4391 |
| - Accuracy: 0.8738 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 256 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 7 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Accuracy | Validation Loss | |
| |:-------------:|:-----:|:----:|:--------:|:---------------:| |
| | 2.6781 | 0.99 | 47 | 0.5475 | 1.8040 | |
| | 1.3191 | 1.99 | 94 | 0.745 | 0.9501 | |
| | 1.078 | 2.98 | 141 | 0.7969 | 0.7767 | |
| | 0.9125 | 3.99 | 188 | 0.6060 | 0.8406 | |
| | 0.7527 | 4.99 | 235 | 0.5214 | 0.8575 | |
| | 0.6852 | 5.98 | 282 | 0.4588 | 0.8656 | |
| | 0.6233 | 6.98 | 329 | 0.4391 | 0.8738 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.28.1 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.3 |
|
|
