bzikst / wav2vec2-large-xlsr-53-gender-recognition-librispeech

Gender recognition for audio files

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Run time and cost

This model costs approximately $0.00022 to run on Replicate, or 4545 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 1 seconds.

Readme

wav2vec2-large-xlsr-53-gender-recognition-librispeech

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on Librispeech-clean-100 for gender recognition. It achieves the following results on the evaluation set: - Loss: 0.0061 - F1: 0.9993

Training and evaluation data

The Librispeech-clean-100 dataset was used to train the model, with 70% of the data used for training, 10% for validation, and 20% for testing.

Training hyperparameters

The following hyperparameters were used during training: - learning_rate: 3e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1 - mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1
0.002 1.0 1248 0.0061 0.9993

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.0+cu118
  • Tokenizers 0.13.3

See more on huggingface:
https://huggingface.co/alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech