metadata
base_model: microsoft/wavlm-base
tags:
- audio-classification
- deepfake
- audio-spoof
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavlm-base-960h-asv19-deepfake
results: []
wavlm-base-960h-asv19-deepfake
This model is a fine-tuned version of microsoft/wavlm-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0161
- Accuracy: 0.9979
- Far: 0.0153
- Frr: 0.0006
- Eer: 0.0080
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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Far | Frr | Eer |
|---|---|---|---|---|---|---|---|
| 0.0386 | 0.79 | 5000 | 0.0597 | 0.9895 | 0.1001 | 0.0003 | 0.0502 |
| 0.0196 | 1.58 | 10000 | 0.0269 | 0.9962 | 0.0326 | 0.0005 | 0.0165 |
| 0.0128 | 2.36 | 15000 | 0.0479 | 0.9938 | 0.0585 | 0.0002 | 0.0294 |
| 0.0152 | 3.15 | 20000 | 0.0119 | 0.9983 | 0.0067 | 0.0011 | 0.0039 |
| 0.0074 | 3.94 | 25000 | 0.0161 | 0.9979 | 0.0153 | 0.0006 | 0.0080 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.2