deepfake_vs_real_image_detection_v2
This model is a fine-tuned version of dima806/deepfake_vs_real_image_detection on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.7467
- eval_model_preparation_time: 0.003
- eval_accuracy: 0.6448
- eval_runtime: 214.8807
- eval_samples_per_second: 224.259
- eval_steps_per_second: 28.034
- step: 0
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: 1e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for griseldans/deepfake_vs_real_image_detection_v2
Base model
google/vit-base-patch16-224-in21k Finetuned
dima806/deepfake_vs_real_image_detection