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wav2vec2-base-1

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

  • Loss: 0.9254
  • Wer: 0.3216

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.6597 2.2 1000 0.8904 0.5388
0.4751 4.41 2000 0.7009 0.3976
0.3307 6.61 3000 0.7068 0.3672
0.2574 8.81 4000 0.7320 0.3544
0.2096 11.01 5000 0.7803 0.3418
0.177 13.22 6000 0.7768 0.3423
0.1521 15.42 7000 0.8113 0.3375
0.1338 17.62 8000 0.8153 0.3325
0.1168 19.82 9000 0.8851 0.3306
0.104 22.03 10000 0.8811 0.3277
0.0916 24.23 11000 0.8722 0.3254
0.083 26.43 12000 0.9527 0.3265
0.0766 28.63 13000 0.9254 0.3216

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.13.3
  • Tokenizers 0.10.3
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Dataset used to train jiobiala24/wav2vec2-base-1