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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:...

KindOtherBase modelGustking/wav2vec2-large-xlsr-deepfake-audio-classificationVersionRevision da7de04

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 LossEpochStepValidation LossAccuracyF1PrecisionRecallRoc AucEer
1.47070.42641000.75300.82180.81590.86860.82180.99640.0309
1.47070.85292000.59320.83940.83510.87840.83940.99830.0181
1.47071.27723000.85080.82760.82240.87180.82760.99810.0141
1.47071.70364000.67780.86580.86330.89420.86580.99440.0211
0.31052.12795000.56780.89060.88930.91020.89060.99500.0171

Framework versions

  • Transformers 5.2.0
  • Pytorch 2.10.0+cu130
  • Datasets 4.6.1
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrimaryVersion da7de04e607deead5027fa41390c5e8084025f7b
huggingface.co/Dax99993/deepfake-spanish-wav2vec2-linear-noaugmented/tree/da7de04e607deead5027fa41390c5e8084025f7b

Verified Sep 13

Model artifacts

1 artifact

model.safetensors

safetensors · 1.18 GB · SHA-256 d0ecf3d36dc2…ee44 · Hugging Face

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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