| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: swin-tiny-patch4-window7-224-uploads-classifier |
| 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: 0.9669421487603306 |
| --- |
| |
| <!-- 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-uploads-classifier |
|
|
| 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: 0.0740 |
| - Accuracy: 0.9669 |
|
|
| ## 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: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.57 | 0.99 | 17 | 1.0733 | 0.7355 | |
| | 0.5726 | 1.97 | 34 | 0.4882 | 0.8347 | |
| | 0.213 | 2.96 | 51 | 0.1166 | 0.9628 | |
| | 0.1528 | 4.0 | 69 | 0.1640 | 0.9339 | |
| | 0.1243 | 4.99 | 86 | 0.1529 | 0.9380 | |
| | 0.0985 | 5.97 | 103 | 0.1888 | 0.9215 | |
| | 0.0838 | 6.96 | 120 | 0.1224 | 0.9421 | |
| | 0.0667 | 8.0 | 138 | 0.1046 | 0.9421 | |
| | 0.0455 | 8.99 | 155 | 0.0740 | 0.9669 | |
| | 0.0469 | 9.97 | 172 | 0.0781 | 0.9669 | |
| | 0.0472 | 10.96 | 189 | 0.1143 | 0.9628 | |
| | 0.0378 | 12.0 | 207 | 0.1974 | 0.9545 | |
| | 0.0386 | 12.99 | 224 | 0.1051 | 0.9587 | |
| | 0.035 | 13.97 | 241 | 0.0719 | 0.9545 | |
| | 0.0339 | 14.96 | 258 | 0.1225 | 0.9504 | |
| | 0.0292 | 16.0 | 276 | 0.0962 | 0.9587 | |
| | 0.0278 | 16.99 | 293 | 0.1322 | 0.9463 | |
| | 0.0233 | 17.97 | 310 | 0.1064 | 0.9545 | |
| | 0.028 | 18.96 | 327 | 0.1207 | 0.9504 | |
| | 0.0269 | 19.71 | 340 | 0.1161 | 0.9504 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.28.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
|
|
