| --- |
| license: apache-2.0 |
| base_model: microsoft/swin-tiny-patch4-window7-224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: swin-tiny-patch4-window7-224 |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.78 |
| - name: Precision |
| type: precision |
| value: 0.7896499764558155 |
| - name: Recall |
| type: recall |
| value: 0.78 |
| --- |
| |
| <!-- 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 |
|
|
| 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: 0.5118 |
| - Accuracy: 0.78 |
| - Precision: 0.7896 |
| - Recall: 0.78 |
| - F1 Score: 0.7315 |
|
|
| ## 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: 7 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
| | No log | 1.0 | 8 | 0.5696 | 0.7333 | 0.5378 | 0.7333 | 0.6205 | |
| | 0.6683 | 2.0 | 16 | 0.5635 | 0.7333 | 0.5378 | 0.7333 | 0.6205 | |
| | 0.5797 | 3.0 | 24 | 0.5584 | 0.7333 | 0.5378 | 0.7333 | 0.6205 | |
| | 0.5547 | 4.0 | 32 | 0.5732 | 0.7333 | 0.5378 | 0.7333 | 0.6205 | |
| | 0.5165 | 5.0 | 40 | 0.5416 | 0.7583 | 0.7486 | 0.7583 | 0.6959 | |
| | 0.5165 | 6.0 | 48 | 0.5488 | 0.7625 | 0.7561 | 0.7625 | 0.7034 | |
| | 0.4893 | 7.0 | 56 | 0.5512 | 0.7583 | 0.7432 | 0.7583 | 0.7003 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.33.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
|
|
