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This model was trained from scratch on the librispeech_asr dataset. It achieves the following results on the evaluation set:

  • Loss: 12.2365
  • Wer: 1.0

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 3.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
6.5774 0.28 500 10.5449 1.0
6.706 0.56 1000 9.4411 1.0
6.9182 0.84 1500 10.9554 1.0
6.7416 1.12 2000 10.0801 1.0
6.8778 1.4 2500 9.8569 1.0
6.7694 1.68 3000 10.4234 1.0
6.7415 1.96 3500 10.6545 1.0
6.5997 2.24 4000 10.4268 1.0
6.7672 2.52 4500 11.1929 1.0
6.5254 2.8 5000 12.2365 1.0

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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Dataset used to train speech-seq2seq/wav2vec2-2-roberta-large

Evaluation results

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