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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-384 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: DeepFake-image-detection-ViT-384 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# DeepFake-image-detection-ViT-384 |
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This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0272 |
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- Accuracy: 0.9911 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2.5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.0037 | 0.9984 | 546 | 0.0272 | 0.9911 | |
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| 0.0006 | 1.9986 | 1093 | 0.1121 | 0.9644 | |
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| 0.0002 | 2.496 | 1365 | 0.1357 | 0.9582 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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