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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: 0.9599
  • Wer: 0.1442

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: 3e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
6.1431 1.68 1500 6.0870 1.4277
5.498 3.36 3000 5.5505 1.6318
3.575 5.04 4500 3.7856 0.6683
1.7532 6.73 6000 2.4603 0.3576
1.6379 8.41 7500 1.8847 0.2932
1.3145 10.09 9000 1.5027 0.2222
0.8389 11.77 10500 1.2637 0.1855
0.9239 13.45 12000 1.1424 0.1683
0.6666 15.13 13500 1.0562 0.1593
0.5258 16.82 15000 0.9911 0.1489
0.4733 18.5 16500 0.9599 0.1442

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 sanchit-gandhi/wav2vec2-2-rnd

Evaluation results

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