--- license: apache-2.0 base_model: Bisher/wav2vec2_ASV_deepfake_audio_detection tags: - generated_from_trainer model-index: - name: short_name results: [] --- # short_name This model is a fine-tuned version of [Bisher/wav2vec2_ASV_deepfake_audio_detection](https://huggingface.co/Bisher/wav2vec2_ASV_deepfake_audio_detection) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 0.5552 - eval_accuracy: 0.895 - eval_precision: 0.9061 - eval_recall: 0.895 - eval_f1: 0.8500 - eval_TP: 1 - eval_TN: 178 - eval_FN: 21 - eval_FP: 0 - eval_EER: 0.2727 - eval_min_tDCF: 0.0281 - eval_auc_roc: 0.7296 - eval_runtime: 66.7052 - eval_samples_per_second: 2.998 - eval_steps_per_second: 2.998 - epoch: 0.04 - step: 1 ## 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: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 2 - mixed_precision_training: Native AMP ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cpu - Datasets 2.21.0 - Tokenizers 0.19.1