| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: SWIN-AI-Image-Detector |
| | results: [] |
| | --- |
| | |
| | <!-- 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-AI-Image-Detector |
| |
|
| | This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0461 |
| | - Accuracy: 0.9833 |
| |
|
| | ## 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: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.2411 | 1.0 | 547 | 0.2430 | 0.9013 | |
| | | 0.2011 | 2.0 | 1094 | 0.1053 | 0.9593 | |
| | | 0.1722 | 3.0 | 1641 | 0.0825 | 0.9671 | |
| | | 0.1424 | 4.0 | 2188 | 0.0851 | 0.9686 | |
| | | 0.1244 | 5.0 | 2735 | 0.0714 | 0.9733 | |
| | | 0.1089 | 6.0 | 3282 | 0.0712 | 0.9734 | |
| | | 0.1047 | 7.0 | 3829 | 0.0461 | 0.9833 | |
| | | 0.1079 | 8.0 | 4376 | 0.0454 | 0.9829 | |
| | | 0.0805 | 9.0 | 4923 | 0.0577 | 0.9790 | |
| | | 0.0778 | 10.0 | 5470 | 0.0539 | 0.9807 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.0 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.13.3 |
| |
|
