| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: swin-tiny-patch4-window7-224-uploads-classifier-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: 0.984313725490196 |
| --- |
| |
| <!-- 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-v2 |
|
|
| 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: 0.0745 |
| - Accuracy: 0.9843 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.2482 | 1.0 | 18 | 0.4781 | 0.8824 | |
| | 0.3036 | 2.0 | 36 | 0.0936 | 0.9804 | |
| | 0.1687 | 3.0 | 54 | 0.0745 | 0.9843 | |
| | 0.1392 | 4.0 | 72 | 0.0980 | 0.9725 | |
| | 0.14 | 5.0 | 90 | 0.0778 | 0.9765 | |
| | 0.1186 | 6.0 | 108 | 0.0837 | 0.9725 | |
| | 0.1088 | 7.0 | 126 | 0.0645 | 0.9804 | |
| | 0.0789 | 8.0 | 144 | 0.0675 | 0.9765 | |
| | 0.0644 | 9.0 | 162 | 0.0940 | 0.9686 | |
| | 0.0582 | 10.0 | 180 | 0.0879 | 0.9725 | |
| | 0.0591 | 11.0 | 198 | 0.0935 | 0.9686 | |
| | 0.0538 | 12.0 | 216 | 0.0540 | 0.9804 | |
| | 0.0588 | 13.0 | 234 | 0.0725 | 0.9686 | |
| | 0.0538 | 14.0 | 252 | 0.0637 | 0.9765 | |
| | 0.0462 | 15.0 | 270 | 0.0694 | 0.9725 | |
| | 0.0352 | 16.0 | 288 | 0.0771 | 0.9686 | |
| | 0.0536 | 17.0 | 306 | 0.0629 | 0.9804 | |
| | 0.0403 | 18.0 | 324 | 0.0933 | 0.9686 | |
| | 0.0412 | 19.0 | 342 | 0.0848 | 0.9725 | |
| | 0.0305 | 20.0 | 360 | 0.0820 | 0.9725 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.28.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
|
|
