Deepfake Spanish Wav2vec2 Linear Noaugmented
This model is a fine-tuned version of Gustking/wav2vec2-large-xlsr-deepfake-audio-classification on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.5678 Accuracy: 0.8906 F1:...
Model source
- Kind
- Other
- File size
- 1.18 GB
- Base model
- Gustking/wav2vec2-large-xlsr-deepfake-audio-classification
- Version
- vRevision da7de04
- Updated
- Sep 13, 2026
- Downloads
- 5
- Source
- Hugging Face
Source description
deepfake-spanish-wav2vec2-linear-noaugmented
This model is a fine-tuned version of Gustking/wav2vec2-large-xlsr-deepfake-audio-classification on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5678
- Accuracy: 0.8906
- F1: 0.8893
- Precision: 0.9102
- Recall: 0.8906
- Roc Auc: 0.9950
- Eer: 0.0171
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: 32
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 75
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc | Eer |
|---|---|---|---|---|---|---|---|---|---|
| 1.4707 | 0.4264 | 100 | 0.7530 | 0.8218 | 0.8159 | 0.8686 | 0.8218 | 0.9964 | 0.0309 |
| 1.4707 | 0.8529 | 200 | 0.5932 | 0.8394 | 0.8351 | 0.8784 | 0.8394 | 0.9983 | 0.0181 |
| 1.4707 | 1.2772 | 300 | 0.8508 | 0.8276 | 0.8224 | 0.8718 | 0.8276 | 0.9981 | 0.0141 |
| 1.4707 | 1.7036 | 400 | 0.6778 | 0.8658 | 0.8633 | 0.8942 | 0.8658 | 0.9944 | 0.0211 |
| 0.3105 | 2.1279 | 500 | 0.5678 | 0.8906 | 0.8893 | 0.9102 | 0.8906 | 0.9950 | 0.0171 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu130
- Datasets 4.6.1
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVerified Sep 13
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- library_name: transformers license: apache-2.0 base_model: Gustking/wav2vec2-large-xlsr-deepfake-audio-classification tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: deepfake-spanish-wav2vec2-linear-noaugmented results: [] --- <!-- 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. --> # deepfake-spanish-wav2vec2-linear-noaugmented This model is a fine-tuned version of [Gustking/wav2vec2-large-xlsr-deepfake-audio-classification](https://huggingface.co/Gustking/wav2vec2-large-xlsr-deepfake-audio-classification) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5678 - Accuracy: 0.8906 - F1: 0.8893 - Precision: 0.9102 - Recall: 0.8906 - Roc Auc: 0.9950 - Eer: 0.0171 ## 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: 32 - eval_batch_size: 48 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 75 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc | Eer | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|:------:| | 1.4707 | 0.4264 | 100 | 0.7530 | 0.8218 | 0.8159 | 0.8686 | 0.8218 | 0.9964 | 0.0309 | | 1.4707 | 0.8529 | 200 | 0.5932 | 0.8394 | 0.8351 | 0.8784 | 0.8394 | 0.9983 | 0.0181 | | 1.4707 | 1.2772 | 300 | 0.8508 | 0.8276 | 0.8224 | 0.8718 | 0.8276 | 0.9981 | 0.0141 | | 1.4707 | 1.7036 | 400 | 0.6778 | 0.8658 | 0.8633 | 0.8942 | 0.8658 | 0.9944 | 0.0211 | | 0.3105 | 2.1279 | 500 | 0.5678 | 0.8906 | 0.8893 | 0.9102 | 0.8906 | 0.9950 | 0.0171 | ### Framework versions - Transformers 5.2.0 - Pytorch 2.10.0+cu130 - Datasets 4.6.1 - Tokenizers 0.22.2
Source context: 5 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo Dax99993/deepfake-spanish-wav2vec2-linear-noaugmented
