deepfake-spanish-wav2vec2-linear-augmented

Dax99993/deepfake-spanish-wav2vec2-linear-augmented

deepfake-spanish-wav2vec2-linear-augmented is a audio classification model from Dax99993. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. 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

Task: Audio Classification
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Mar 2, 2026
Updated: Mar 2, 2026
SHA: 3ebcd4b2

Base models

Gustking/wav2vec2-large-xlsr-deepfake-audio-classification

Model card

From the Hugging Face model README

deepfake-spanish-wav2vec2-linear-augmented

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: 0.4476
Accuracy: 0.9090
F1: 0.9083
Precision: 0.9230
Recall: 0.9090
Roc Auc: 0.9994
Eer: 0.0048

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
2.1469	0.2133	100	0.4042	0.8847	0.8832	0.9063	0.8847	0.9965	0.0285
2.1469	0.4267	200	0.3700	0.8874	0.8860	0.9081	0.8874	0.9984	0.0163
2.1469	0.64	300	0.5706	0.8837	0.8821	0.9056	0.8837	0.9974	0.0123
2.1469	0.8533	400	0.3749	0.9128	0.9121	0.9257	0.9128	0.9995	0.0059
0.6001	1.0661	500	0.3203	0.9232	0.9227	0.9334	0.9232	0.9996	0.0043
0.6001	1.2795	600	0.3738	0.9168	0.9162	0.9286	0.9168	0.9994	0.0048
0.6001	1.4928	700	0.3272	0.9304	0.9300	0.9389	0.9304	0.9976	0.0099
0.6001	1.7061	800	0.4476	0.9090	0.9083	0.9230	0.9090	0.9994	0.0048

Framework versions

Transformers 5.2.0
Pytorch 2.10.0+cu130
Datasets 4.6.1
Tokenizers 0.22.2

Task: Audio Classification
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Mar 2, 2026
Updated: Mar 2, 2026