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wav2vec2-large-mms-1b-russian-colab

This model is a fine-tuned version of facebook/mms-1b-all on the common_voice_6_1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1305
  • Wer: 0.1798

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: 0.001
  • 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: 100
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.4789 0.21 100 0.1676 0.2126
0.2042 0.41 200 0.1507 0.2010
0.1991 0.62 300 0.1460 0.1989
0.1882 0.83 400 0.1464 0.1992
0.1804 1.03 500 0.1402 0.1900
0.1809 1.24 600 0.1404 0.1890
0.1787 1.45 700 0.1392 0.1873
0.1781 1.65 800 0.1413 0.1926
0.1767 1.86 900 0.1411 0.1883
0.1779 2.07 1000 0.1375 0.1853
0.1749 2.27 1100 0.1356 0.1845
0.1749 2.48 1200 0.1343 0.1836
0.1652 2.69 1300 0.1339 0.1826
0.1677 2.89 1400 0.1334 0.1826
0.1764 3.1 1500 0.1333 0.1832
0.1697 3.31 1600 0.1320 0.1811
0.1678 3.51 1700 0.1313 0.1804
0.165 3.72 1800 0.1308 0.1799
0.1641 3.93 1900 0.1305 0.1798

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Evaluation results