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wav2vec2-large-xls-r-300m-vi-25p

This model was trained from scratch on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8293
  • Wer: 0.4109

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: 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: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.9542 1.31 400 1.4443 0.5703
1.276 2.62 800 1.4606 0.5736
1.1311 3.93 1200 1.4552 0.5186
0.9519 5.25 1600 1.4477 0.5300
0.8293 6.56 2000 1.4166 0.5097
0.7555 7.87 2400 1.4100 0.4906
0.6724 9.18 2800 1.4982 0.4880
0.6038 10.49 3200 1.4524 0.4945
0.5338 11.8 3600 1.4995 0.4798
0.4988 13.11 4000 1.6715 0.4653
0.461 14.43 4400 1.5699 0.4552
0.4154 15.74 4800 1.5762 0.4557
0.3822 17.05 5200 1.5978 0.4471
0.3466 18.36 5600 1.6579 0.4512
0.3226 19.67 6000 1.6825 0.4378
0.2885 20.98 6400 1.7376 0.4421
0.2788 22.29 6800 1.7150 0.4300
0.249 23.61 7200 1.7073 0.4263
0.2317 24.92 7600 1.7349 0.4200
0.2171 26.23 8000 1.7419 0.4186
0.1963 27.54 8400 1.8438 0.4144
0.1906 28.85 8800 1.8293 0.4109

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu113
  • Datasets 1.18.3
  • Tokenizers 0.10.3
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Dataset used to train leviethoang/graduation-reserach-1-demo