deepfake_vs_real_image_detection_v2

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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