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To rerun this experiment, please clone this directory and run:

python create_model.py

followed by

./run_librispeech.sh

wav2vec2-2-bart-large

This model is a fine-tuned version of facebook/wav2vec2-large-lv60 and bart-large on the librispeech_asr - clean dataset.

It achieves the following results on the evaluation set:

  • Loss: 0.3204
  • Wer: 0.0486

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: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 4
  • gradient_accumulation_steps: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

See Training Metrics Tab.

Framework versions

  • Transformers 4.15.0.dev0
  • Pytorch 1.9.0+cu111
  • Datasets 1.16.2.dev0
  • Tokenizers 0.10.3
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