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Wav2Vec2 Large Wolof

This model is a fine-tuned version of facebook/wav2vec2-large on the serge-wilson/wolof_speech_transcription dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.2516
  • eval_wer: 22.3681
  • eval_runtime: 224.3149
  • eval_samples_per_second: 10.008
  • eval_steps_per_second: 1.253
  • epoch: 13.96
  • step: 5500

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 20

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.0
  • Datasets 2.14.5
  • Tokenizers 0.14.0
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Dataset used to train serge-wilson/wav2vec-large-wolof