deep_fake_model
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: 0.0605
- Accuracy: 0.9979
- F1-score: 0.9979
- Recall-score: 0.9979
- Precision-score: 0.9979
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: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Recall-score | Precision-score |
---|---|---|---|---|---|---|---|
1.9553 | 0.992 | 31 | 1.9020 | 0.3507 | 0.2502 | 0.3507 | 0.3103 |
1.8002 | 1.984 | 62 | 1.6493 | 0.4743 | 0.4116 | 0.4743 | 0.6029 |
1.4882 | 2.976 | 93 | 1.2879 | 0.5693 | 0.4839 | 0.5693 | 0.5924 |
1.1849 | 4.0 | 125 | 1.0308 | 0.7614 | 0.7370 | 0.7614 | 0.7530 |
0.9838 | 4.992 | 156 | 0.8273 | 0.8214 | 0.7817 | 0.8214 | 0.8209 |
0.6932 | 5.984 | 187 | 0.5542 | 0.8986 | 0.8829 | 0.8986 | 0.9127 |
0.4819 | 6.976 | 218 | 0.3752 | 0.9707 | 0.9708 | 0.9707 | 0.9716 |
0.2839 | 8.0 | 250 | 0.2012 | 0.9929 | 0.9928 | 0.9929 | 0.9930 |
0.1833 | 8.992 | 281 | 0.1280 | 0.9964 | 0.9964 | 0.9964 | 0.9964 |
0.1333 | 9.984 | 312 | 0.1403 | 0.9836 | 0.9835 | 0.9836 | 0.9841 |
0.1029 | 10.9760 | 343 | 0.0846 | 0.9964 | 0.9964 | 0.9964 | 0.9964 |
0.08 | 12.0 | 375 | 0.0793 | 0.995 | 0.9950 | 0.995 | 0.9950 |
0.0724 | 12.992 | 406 | 0.0973 | 0.9886 | 0.9885 | 0.9886 | 0.9887 |
0.0663 | 13.984 | 437 | 0.0668 | 0.9964 | 0.9964 | 0.9964 | 0.9964 |
0.0617 | 14.88 | 465 | 0.0605 | 0.9979 | 0.9979 | 0.9979 | 0.9979 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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