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wav2vec2-xls-r-300m-CV8-ro

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - RO dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1578
  • Wer: 0.6040
  • Cer: 0.0475

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: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
2.9736 3.62 500 2.9508 1.0 1.0
1.3293 7.25 1000 0.3330 0.8407 0.0862
0.956 10.87 1500 0.2042 0.6872 0.0602
0.9509 14.49 2000 0.2184 0.7088 0.0652
0.9272 18.12 2500 0.2312 0.7211 0.0703
0.8561 21.74 3000 0.2158 0.6838 0.0631
0.8258 25.36 3500 0.1970 0.6844 0.0601
0.7993 28.98 4000 0.1895 0.6698 0.0577
0.7525 32.61 4500 0.1845 0.6453 0.0550
0.7211 36.23 5000 0.1781 0.6274 0.0531
0.677 39.85 5500 0.1732 0.6188 0.0514
0.6517 43.48 6000 0.1691 0.6177 0.0503
0.6326 47.1 6500 0.1619 0.6045 0.0479

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0
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Dataset used to train ubamba98/wav2vec2-xls-r-300m-CV8-ro