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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: 18.7898
  • 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
6.5396 0.28 500 9.0401 1.0120
5.898 0.56 1000 9.3199 1.0
4.9595 0.84 1500 8.4434 1.4563
5.7082 1.12 2000 15.1805 1.0000
5.4377 1.4 2500 15.7984 1.0021
5.5941 1.68 3000 18.4928 1.0
5.0662 1.96 3500 17.4886 1.0000
4.8363 2.24 4000 18.9458 1.0
4.7908 2.52 4500 18.2794 1.0006
4.679 2.8 5000 18.7898 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-bart-large-no-adapter-frozen-enc

Evaluation results

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