| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: VIT_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. --> |
| |
|
| | # VIT_AI_image_detector |
| | |
| | This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0295 |
| | - Accuracy: 0.9924 |
| | |
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 64 |
| | - 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.1686 | 1.0 | 1093 | 0.0843 | 0.9697 | |
| | | 0.1195 | 2.0 | 2187 | 0.0731 | 0.9728 | |
| | | 0.072 | 3.0 | 3281 | 0.0543 | 0.9803 | |
| | | 0.1072 | 4.0 | 4375 | 0.0348 | 0.9884 | |
| | | 0.079 | 5.0 | 5468 | 0.0342 | 0.9886 | |
| | | 0.0681 | 6.0 | 6562 | 0.0317 | 0.9903 | |
| | | 0.0513 | 7.0 | 7656 | 0.0304 | 0.9914 | |
| | | 0.0518 | 8.0 | 8750 | 0.0293 | 0.9916 | |
| | | 0.0674 | 9.0 | 9843 | 0.0295 | 0.9924 | |
| | | 0.058 | 9.99 | 10930 | 0.0313 | 0.9917 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.30.0 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.13.3 |
| | |
