deepfake-audio-detector-v9 – AI Model by ANANDAPADMANABHANANS | AlphaNeural AI

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ANANDAPADMANABHANANS/
deepfake-audio-detector-v9

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audio-classification

generated_from_trainer

Hemgg/Deepfake-audio-detection

endpoints_compatible

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deepfake-audio-detector-v9

This model is a fine-tuned version of Heem2/Deepfake-audio-detection on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6505
Accuracy: 0.6322
Precision: 0.5973
Recall: 0.8117
F1: 0.6882

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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.7265	1.0	571	0.6450	0.6160	0.5912	0.7522	0.6620
0.6481	2.0	1142	0.6483	0.6265	0.5922	0.8126	0.6851
0.6273	3.0	1713	0.6388	0.6327	0.6011	0.7890	0.6823
0.616	4.0	2284	0.6462	0.6327	0.5987	0.8047	0.6866
0.6064	5.0	2855	0.6505	0.6322	0.5973	0.8117	0.6882

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2