| | --- |
| | license: apache-2.0 |
| | base_model: microsoft/swin-tiny-patch4-window7-224 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: swin-tiny-patch4-window7-224-MM_Classification |
| | 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: 0.8915401301518439 |
| | --- |
| | |
| | <!-- 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-MM_Classification |
| | |
| | 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: 0.2895 |
| | - Accuracy: 0.8915 |
| | |
| | ## 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: 128 |
| | - eval_batch_size: 128 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 512 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 1.0635 | 0.9846 | 16 | 0.7524 | 0.6725 | |
| | | 0.4571 | 1.9692 | 32 | 0.3692 | 0.8742 | |
| | | 0.3819 | 2.9538 | 48 | 0.3500 | 0.8688 | |
| | | 0.3278 | 4.0 | 65 | 0.3158 | 0.8796 | |
| | | 0.2941 | 4.9846 | 81 | 0.2886 | 0.8883 | |
| | | 0.2912 | 5.9692 | 97 | 0.2895 | 0.8915 | |
| | | 0.2575 | 6.9538 | 113 | 0.2801 | 0.8839 | |
| | | 0.2604 | 8.0 | 130 | 0.2847 | 0.8861 | |
| | | 0.2519 | 8.9846 | 146 | 0.2804 | 0.8872 | |
| | | 0.2592 | 9.8462 | 160 | 0.2795 | 0.8872 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.43.2 |
| | - Pytorch 1.13.1+cu117 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
