| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: swin-tiny-patch4-window7-224-LongSleeveCleanedData |
| | 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: 0.9966480446927374 |
| | --- |
| | |
| | <!-- 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-LongSleeveCleanedData |
| |
|
| | 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: 0.0110 |
| | - Accuracy: 0.9966 |
| |
|
| | ## 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: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 7 |
| | - total_train_batch_size: 56 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.01 |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.1802 | 0.99 | 143 | 0.1151 | 0.9598 | |
| | | 0.0836 | 2.0 | 287 | 0.0202 | 0.9944 | |
| | | 0.1186 | 3.0 | 431 | 0.0165 | 0.9944 | |
| | | 0.08 | 4.0 | 575 | 0.0110 | 0.9966 | |
| | | 0.0575 | 4.97 | 715 | 0.0125 | 0.9955 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.1 |
| | - Pytorch 2.0.0+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| |
|
