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

  • Loss: 0.6693
  • Wer: 0.5921

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: 7.5e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 500.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.9504 18.18 400 4.6730 1.0
3.3766 36.36 800 3.3464 1.0
3.1128 54.55 1200 3.0177 0.9980
1.7966 72.73 1600 0.8733 0.8039
1.4085 90.91 2000 0.5555 0.6458
1.1731 109.09 2400 0.4930 0.6438
1.0271 127.27 2800 0.4780 0.6093
0.9045 145.45 3200 0.4647 0.6578
0.807 163.64 3600 0.4505 0.5925
0.741 181.82 4000 0.4746 0.6025
0.6706 200.0 4400 0.5004 0.5844
0.6186 218.18 4800 0.4984 0.5997
0.5508 236.36 5200 0.5298 0.5636
0.5123 254.55 5600 0.5410 0.5110
0.4623 272.73 6000 0.5591 0.5383
0.4281 290.91 6400 0.5775 0.5600
0.4045 309.09 6800 0.5924 0.5580
0.3651 327.27 7200 0.5671 0.5684
0.343 345.45 7600 0.6083 0.5945
0.3085 363.64 8000 0.6243 0.5728
0.2941 381.82 8400 0.6245 0.5580
0.2735 400.0 8800 0.6458 0.5804
0.262 418.18 9200 0.6566 0.5824
0.2578 436.36 9600 0.6558 0.5965
0.2388 454.55 10000 0.6598 0.5993
0.2328 472.73 10400 0.6700 0.6041
0.2286 490.91 10800 0.6684 0.5957

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.4.dev0
  • Tokenizers 0.11.0
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Dataset used to train anuragshas/wav2vec2-xls-r-300m-mr-cv8-with-lm

Evaluation results

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