codewithRiz / deep_fake_model_aug

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Model's Last Updated: July 29 2024
audio-classification

Introduction of deep_fake_model_aug

Model Details of deep_fake_model_aug

deep_fake_model_aug

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1637
  • Accuracy: 0.95
  • F1-score: 0.9499
  • Recall-score: 0.95
  • Precision-score: 0.9508
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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy F1-score Recall-score Precision-score
0.5477 0.9956 140 0.4459 0.796 0.7950 0.796 0.8078
0.3685 1.9982 281 0.2871 0.908 0.9080 0.908 0.9081
0.2392 2.9938 421 0.1878 0.944 0.9439 0.944 0.9449
0.1566 3.9964 562 0.1637 0.95 0.9499 0.95 0.9508
0.1131 4.9778 700 0.1594 0.95 0.9499 0.95 0.9511
Framework versions
  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1

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https://huggingface.co/codewithRiz/deep_fake_model_aug

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https://huggingface.co/codewithRiz/deep_fake_model_aug

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