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wav2vec2-base-gn-demo

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: 0.7426
  • Wer: 0.7256

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine_with_restarts
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 60
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 4.0 100 0.7045 0.7409
No log 8.0 200 0.7200 0.75
No log 12.0 300 0.7400 0.7439
No log 16.0 400 0.7677 0.7515
0.0846 20.0 500 0.7765 0.7271
0.0846 24.0 600 0.7821 0.7287
0.0846 28.0 700 0.7671 0.7180
0.0846 32.0 800 0.7594 0.7180
0.0846 36.0 900 0.7500 0.7165
0.0713 40.0 1000 0.7351 0.7287
0.0713 44.0 1100 0.7361 0.7241
0.0713 48.0 1200 0.7389 0.7378
0.0713 52.0 1300 0.7424 0.7210
0.0713 56.0 1400 0.7425 0.7256
0.0669 60.0 1500 0.7426 0.7256

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.3
  • Tokenizers 0.10.3
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Datasets used to train azuur/wav2vec2-base-gn-demo