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wav2vec2_common_voice_accents_4

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0047

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: 0.0003
  • train_batch_size: 48
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 384
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
4.615 1.28 400 0.8202
0.3778 2.56 800 0.1587
0.2229 3.85 1200 0.1027
0.1799 5.13 1600 0.0879
0.1617 6.41 2000 0.0772
0.1474 7.69 2400 0.0625
0.134 8.97 2800 0.0498
0.1213 10.26 3200 0.0429
0.1186 11.54 3600 0.0434
0.1118 12.82 4000 0.0312
0.1026 14.1 4400 0.0365
0.0951 15.38 4800 0.0321
0.0902 16.67 5200 0.0262
0.0843 17.95 5600 0.0208
0.0744 19.23 6000 0.0140
0.0718 20.51 6400 0.0204
0.0694 21.79 6800 0.0133
0.0636 23.08 7200 0.0104
0.0609 24.36 7600 0.0084
0.0559 25.64 8000 0.0050
0.0527 26.92 8400 0.0089
0.0495 28.21 8800 0.0058
0.0471 29.49 9200 0.0047

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.4
  • Tokenizers 0.11.6
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Dataset used to train willcai/wav2vec2_common_voice_accents_4