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Deepfake-Audio-Detection-v1 – AI Model by Zeyadd-Mostaffa | AlphaNeural AI
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Zeyadd-Mostaffa
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Deepfake-Audio-Detection-v1
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transformers
safetensors
wav2vec2
audio-classification
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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Deepfake-Audio-Detection-v1
This model is a fine-tuned version of
facebook/wav2vec2-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0187
Accuracy: 0.9966
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: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1329
1.0
407
0.1110
0.9624
0.0348
2.0
814
0.0319
0.9911
0.0082
3.0
1221
0.0165
0.9966
0.0085
4.0
1628
0.0230
0.9957
0.0002
5.0
2035
0.0187
0.9966
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
