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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: 4.6263
  • Wer: 0.8568

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
5.9849 1.68 1500 5.9623 1.1028
5.1696 3.36 3000 5.5504 1.6345
4.1412 5.04 4500 5.3853 1.3565
2.7226 6.73 6000 5.3072 0.9908
3.2607 8.41 7500 5.4121 1.2854
2.4017 10.09 9000 5.1094 1.0303
1.7361 11.77 10500 4.8928 0.9506
2.0638 13.45 12000 4.8352 0.9127
1.2832 15.13 13500 4.7271 0.9103
1.0439 16.82 15000 4.5980 0.8720
0.4112 18.5 16500 4.6263 0.8568

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-2-layer-bart

Evaluation results

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