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wav2vec2-large-xls-r-300m-bashkir

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - BA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1892
  • Wer: 0.2421

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: 32
  • eval_batch_size: 32
  • 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: 10.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4792 0.5 2000 0.4598 0.5404
1.449 1.0 4000 0.4650 0.5610
1.3742 1.49 6000 0.4001 0.4977
1.3375 1.99 8000 0.3916 0.4894
1.2961 2.49 10000 0.3641 0.4569
1.2714 2.99 12000 0.3491 0.4488
1.2399 3.48 14000 0.3151 0.3986
1.2067 3.98 16000 0.3081 0.3923
1.1842 4.48 18000 0.2875 0.3703
1.1644 4.98 20000 0.2840 0.3670
1.161 5.48 22000 0.2790 0.3597
1.1303 5.97 24000 0.2552 0.3272
1.0874 6.47 26000 0.2405 0.3142
1.0613 6.97 28000 0.2352 0.3055
1.0498 7.47 30000 0.2249 0.2910
1.021 7.96 32000 0.2118 0.2752
1.0002 8.46 34000 0.2046 0.2662
0.9762 8.96 36000 0.1969 0.2530
0.9568 9.46 38000 0.1917 0.2449
0.953 9.96 40000 0.1893 0.2425

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0
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Dataset used to train infinitejoy/wav2vec2-large-xls-r-300m-bashkir

Evaluation results