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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: 11.7664
  • Wer: 2.0133

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
5.171 0.28 500 8.6956 2.0055
5.307 0.56 1000 8.5958 2.0096
5.1449 0.84 1500 10.4208 2.0115
6.1351 1.12 2000 10.2950 2.0059
6.2997 1.4 2500 10.6762 2.0115
6.1394 1.68 3000 10.9190 2.0110
6.1868 1.96 3500 11.0166 2.0112
5.9647 2.24 4000 11.4154 2.0141
6.2202 2.52 4500 11.5837 2.0152
5.9612 2.8 5000 11.7664 2.0133

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-bert-large-no-adapter-frozen-enc

Evaluation results

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