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short_name – AI Model by Bisher | AlphaNeural AI

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Bisher/wav2vec2_ASV_deepfake_audio_detection

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short_name

This model is a fine-tuned version of Bisher/wav2vec2_ASV_deepfake_audio_detection on an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 0.5552
eval_accuracy: 0.895
eval_precision: 0.9061
eval_recall: 0.895
eval_f1: 0.8500
eval_TP: 1
eval_TN: 178
eval_FN: 21
eval_FP: 0
eval_EER: 0.2727
eval_min_tDCF: 0.0281
eval_auc_roc: 0.7296
eval_runtime: 66.7052
eval_samples_per_second: 2.998
eval_steps_per_second: 2.998
epoch: 0.04
step: 1

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2
mixed_precision_training: Native AMP

Framework versions

Transformers 4.44.0
Pytorch 2.4.0+cpu
Datasets 2.21.0
Tokenizers 0.19.1