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wav2vec2_ASV_deepfake_audio_detection_DF_finetune_frozen_further
Bisher/wav2vec2_ASV_deepfake_audio_detection_DF_finetune_frozen_further
wav2vec2_ASV_deepfake_audio_detection_DF_finetune_frozen_further is a machine learning model from Bisher. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 24, 2024
- Updated
- Aug 24, 2024
- SHA
- 6cd5852f
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
wav2vec2_ASV_deepfake_audio_detection_DF_finetune_frozen_further
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:
- Loss: 0.3702
- Accuracy: 0.9173
- Precision: 0.9193
- Recall: 0.9173
- F1: 0.8917
- Tp: 384
- Tn: 17889
- Fn: 1623
- Fp: 24
- Eer: 0.0762
- Min Tdcf: 0.0323
- Auc Roc: 0.9561
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: 152
- eval_batch_size: 152
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 608
- 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 | Precision | Recall | F1 | Tp | Tn | Fn | Fp | Eer | Min Tdcf | Auc Roc |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0237 | 0.0490 | 10 | 0.3313 | 0.9162 | 0.9174 | 0.9162 | 0.8897 | 364 | 17886 | 1643 | 27 | 0.0829 | 0.0335 | 0.9725 |
| 0.0219 | 0.0979 | 20 | 0.3291 | 0.9147 | 0.9168 | 0.9147 | 0.8865 | 328 | 17892 | 1679 | 21 | 0.0809 | 0.0328 | 0.9736 |
| 0.0202 | 0.1469 | 30 | 0.3233 | 0.9173 | 0.9189 | 0.9173 | 0.8918 | 386 | 17887 | 1621 | 26 | 0.0765 | 0.0323 | 0.9738 |
| 0.0205 | 0.1958 | 40 | 0.3702 | 0.9173 | 0.9193 | 0.9173 | 0.8917 | 384 | 17889 | 1623 | 24 | 0.0762 | 0.0323 | 0.9561 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Aug 24, 2024
- Updated
- Aug 24, 2024